SURVEILLANCE OF MALFORMATIONS
be concerned with early detection of possible environmental hazards. Only in the last 50 years has the identification of malformed children been seen to be of importance. Although stillbirths were registered in England and Wales from 1927 (RegistrarGeneral, 1929) no causes were recorded until 1960 (Registrar General, 1962). Stillbirths and their causes were registered in Scotland from 1939 (Registrar-General for Scotland, 1944) and studies in the United Kingdom based on the incidence of anencephaly in all births have, until 1960, been based on Scottish births. The number of children who die because of malformations, however, gives no measure of the incidence of malformations present in children, since some malformations are compatible with life. Other malformations predispose children to an increased risk of death unless the condition is treated; and as effective methods of treatment are developed the numbers of children who die diminish (e.g. those with congenital heart disease and spina bifida). Schemes for counting all malformed children have existed in Birmingham since 1949, covering about 20000 births/year (Charles, 1951), and in Liverpool and Bootle since 1959 (about 9000 births/year) (Smithells, 1962). Neither of these schemes involved large enough numbers of births to allow the detection of a change either in frequency over a short period of time or in occurrence of very rare types of malformations. Even a national scheme in Sweden covering 20000-40000 births/year, begun in 1955, did not reveal the thalidomide epidemic at the time, although, in retrospect, increases in the occurrence of limb malformations were detectable during that period (Winberg, 1964).
SURVEILLANCE OF MALFORMATIONS JOSEPHINE A. C. WEATHERALL M.B. Ch.B. B.Sc. M.F.C.M. J. C. HASKEY M.Sc. Office of Population Censuses and Surveys, London 1 2 3 4
Surveillance systems Definitions used in the surveillance of malformations Data processing and monitoring Monitoring in England and Wales a Collection of data b Monitoring of data 5 Further uses of data References
Surveillance and monitoring are often used as though they are synonymous terms. "Surveillance" is defined in The shorter
Oxford English dictionary (SOED) as a "watch or guard kept over . . . a suspected person . . . or the like" and in the Concise Oxford dictionary, more succinctly, as "supervision, close observation or invigilation ". The verb " to monitor " is perhaps 50 years old when used in this context. It was introduced in the field of regulating recorded sound (SOED, 3rd ed., Addenda) and is now used for indicating regular measurements of any continuous process, particularly in situations where some action will be taken following a change. The two terms, surveillance and monitoring, have come to be closely interdependent when used to refer to a programme dealing with problems such as human malformations. In developed countries the nearly ninefold reduction in infant mortality achieved in the last 100 years has left congenital malformations as the largest single cause of infant loss, and attention in public health and medical research has turned towards the prevention of malformations. Between 1920 and 1940, research into the causation of malformation of mammalian offspring turned from genetic factors towards the components of the maternal diet, and the influence of vitamins was investigated (Nelson, 1957; Wilson, 1957). The first clear demonstration, however, that an environmental factor was causally implicated occurred when Gregg (1941) showed that rubella infection of the mother during pregnancy was associated with specific malformations in the subsequently born children. Further evidence about specific factors in the maternal environment was shown in animals by Haskin (1948) with nitrogen mustard and by Gillman, Gilbert, Gillman & Spence (1948) with trypan blue. But these and laterfindingsin animals did not alert toxicologists to the possible occurrence of similar events in human beings until, between 1958 and 1962, an epidemic of babies born with gross limb malformations was shown to be associated with the consumption of thalidomide by the mothers during pregnancy. Since then, awareness that environmental factors can cause abnormalities in babies has influenced persons responsible for health care to
1. Surveillance Systems Since the tragedy of the thalidomide epidemic, two needs have become apparent: first to be on the alert for new factors in the environment that may cause malformations, and secondly to know the persons in a community whose malformations lead them to require special help. These challenges have spurred the development of three main types of information system. One type involves the detailed prospective recording of events and medication during pregnancy for every birth in a given population, so that malformations can be related to events during pregnancy. Such information schemes have been tried in special studies but data collection and analysis are costly. With conditions such as major malformations of the central nervous system (CNS) about 300 normal births have to be recorded in order to find one baby with a defect of this type, even in countries where these defects are common. In countries with all births in hospital and with adequate routine recording of antenatal procedures and medication, the recorded data can be extremely valuable when examinedretrospectivelyfor malformed infants and for control babies (Kallen & Winberg, 1969; Klemetti & Saxen, 1970). Some prospective studies, such as those in West Germany, parts of Scotland, England and Wales and parts of France, have concentrated on collecting information about medicines administered during pregnancy; but the largest of these studies includes only about 15000 births and they lack information about the weeks before women register their pregnancies. A second type of information system involves registering, at birth only, the babies born with malformations to measure the prevalence at birth. Such schemes have been established in England and Wales, Northern Ireland, some parts of the USA, 39
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Josephine A. C. Weatherall&J. C. Haskey
SURVEILLANCE OF MALFORMATIONS
Josephine A. C. Weatherall&J. C. Haskey another medical officer. Alternatively both medical officers may notify the case, giving rise to double recording. Although complete and reliable recording of malformations at birth could be obtained by utilizing multiple sources of information, such as hospital records, midwives' records, local health department records and by re-examining every reported child to confirm the diagnosis, a quicker and less expensive reporting system which accepts unvalidated diagnoses can provide a flow of information which will allow changes in occurrence of malformations to be recognized. The data should be interpreted with reservation; some malformations will be under-reported, some notified with scrupulous care and some over-reported; nevertheless, the variations in reporting can be detected and their significance analysed. Artefacts resulting from the method of reporting are likely to be confined to particular hospitals or areas, whereas environmental factors are not likely to be confined within administrative boundaries.
most provinces of Canada, and recently in many countries which have adopted a statutory medical certificate at birth (e.g. Belgium, France and Denmark). Several countries record all congenital defects, no matter at what age they are discovered, as is done in British Columbia. This sort of system depends on the maintenance of a register of identified persons so that reports from several sources can be collated and a true count of affected persons obtained. This type of information system is essential in order to make estimates of prevalence of malformations which are not obvious at birth and which cause little or no ill health or handicap. The true estimate of many types of malformation cannot be made until all the affected persons have had a reasonable chance of their malformation being found and registered. This system of registration can, however, be used to provide estimates of the prevalence of malformations in the population at any given age. To detect quickly environmental influences that cause malformations it is desirable to analyse the recorded data at frequent intervals, beginning as soon as possible after birth. Most of the schemes for registering malformations at birth have been set up to achieve this end. However, the schemes for recording all cases, detected at any age, have an important complementary role in informing genetic counsellors about the risks of malformed children being born either to persons known themselves to have had malformations or to those who belong to families with affected individuals.
3.
Data Processing and Monitoring
A scheme for notification of malformations, established as an early warning system, must be processed quickly. The system will reflect changes in the efficiencies of reporting and will therefore, unless reporting is validated, not provide a reliable "source" of data for studying epidemiological characteristics. The frequency of analysis of the data and the geographical areas chosen will depend on the total numbers of births involved. Ideally, the birth denominators should be available at the time of analysis, so that incidence rates can be calculated. However where this is not possible, there is no reason why the reported number of malformations should not be examined as a series by themselves, without regard to the denominator. The groupings of malformations used for counting are of great importance. "All reported malformations" is a somewhat complicated category, since one baby may be reported with several different malformations and other babies with only one; in this way the over-all total reflects the thoroughness with which multiple malformations are recorded. Similarly, the figure for "total babies with malformations" is likely to be influenced by the individual reporting officer's concept of what constitutes a malformation, and is likely to vary from area to area. By considering particular types of well-defined malformations in individual areas these disadvantages are minimized. Well-defined categories of malformations, such as babies with cleft palate only, babies with cleft lip only, and babies with both defects, are grouped so that all babies with facial clefts can be counted. Similarly, the well-defined CNS malformations are counted separately and grouped to form the class of all babies with CNS disorders. It is desirable to study the data periodically to find which malformations occur in groups more frequently than by chance, and these non-randomly associated malformations can be used to form new classes for monitoring; and study of them may suggest some new causal factors. The ratio of the rates of serious malformations to all malformations, and the ratio of specific malformations to all malformations, and many other such ratios, may provide useful information about the methods of recording and help in interpreting any observed changes. Although malformation categories are grouped for some purposes into broad classes, such as "all limb defects" or "all disorders of the alimentary tract", it is useful to retain the ability to analyse the exact constituent malformations. Increases in groups formed from congenital dislocation of the
2. Definitions Used in the Surveillance of Malformations In setting up any scheme for counting events, clear definitions of these events are essential. In the field of vital statistics, an event as seemingly precise as a birth may depend on the gestational age or weight of the child and vary in legal definition from country to country. Since malformations themselves are probably a cause of miscarriage or of premature delivery, the precise period of gestation needs to be stipulated. The definitions of a live birth vary, too, and in countries where legal registration takes place only for children alive at some given time after birth the population denominator of live births may need to be corrected if valid comparisons are to be made with countries where the taking of a single breath operates as the criterion of a live birth. Within a given country, however, definitions remain constant and a watch may be kept on the numbers of malformed children being born. Factors such as the thoroughness of post-mortem examinations, especially of stillborn children, will affect the numbers detected and the apparent frequencies of the malformations. The malformations themselves are not always clearly defined. Gross hydrocephaly or anencephaly will not be missed but congenital dislocation of the hip, mongolism, or internal malformations may well go unrecognized unless specially looked for. As several malformations may occur in the same baby it is desirable to allow each to be reported, so that groups of associated malformations may be studied. Both rubella and thalidomide produced characteristic groupings of malformations and the appearance of a new grouping may be thefirstsign of a new teratogenic substance in the environment. Apart from difficulties with definitions and diagnosis there are potential difficulties in the transmission of information both within a hospital and within the system for collecting the data. The local medical officer responsible for recording data in the area of a mother's residence may fail to hear about the birth of her malformed infant in a hospital within the area of 40
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SURVEILLANCE OF MALFORMATIONS
The methods used have not substantially altered since they were described by Hill, Spicer & Weatherall (1968) and by Weatherall (1969). With the reorganization of the National Health Service and conversion of the General Register Office to the Office of Population Censuses and Surveys (OPCS), certain changes have been made. The following describes the statistical systems being used in 1975, and indicates the officers responsible for gathering the primary data.
hip, detection of which depends on the thoroughness with which the baby is examined and on the subjective judgement of the examiner, with the more objectively identifiable polydactyly, syndactyly, reduction deformities and talipes, should not be allowed to cause undue alarm until the reasons for the variation in numbers have been determined. The interpretation of variations in the data sometimes presents difficulties, but an observed increase acts as a stimulus to examine the data more thoroughly to decide whether or not an epidemic has occurred. Any simple monitoring system, such as a chart showing the numbers reported, can be used for surveillance, whilst moresensitive tests can be devised by statisticians to help distinguish true changes due to some external factor from changes due to chance. Such analyses should be both by reporting area and by geographical area, so that increases and decreases due to artefacts in the methods of reporting can be identified quickly. They may thus be distinguished from the more serious possibilities of real epidemic increases. The choice of the methods used in monitoring depends on the type and quantity of the data available. When data are collected, as in England and Wales, in each of a large number of small areas, and for many distinct classes of malformations within each area, an automated computer-based scheme presents the most efficient way of surveillance of the incoming data. Although routine tabulations of the data are produced, the computer is used to perform routine statistical tests to detect increases and decreases, and only the statistically significant results are reported. An appropriate model is needed to describe the statistical distribution of the monthly numbers of malformations and once this is identified reliable statistical tests may be chosen. Malformations that occur relatively frequently, such as anencephaly and talipes, with approximate incidence rates of 1300 and 3800 per million total births, respectively, provide incidence rates of several cases per month in a typical area; this is large enough to permit quick detection of changes in the mean level. Some of the important malformations, however, are quite rare, e.g. anophthalmos and microphthalmos; and to detect such malformations, which occur at a rate of about 40 per million total births, it is generally necessary to observe the occurrence in much larger groups, in order that a true change in the incidence of the malformation may be revealed. Such large groups of births can be obtained only by aggregating births from wide geographical areas occurring at a specific time, or by analysing data collected over long time-periods. The essential factors for a monitoring system are, therefore: consistency in the recording of events, minimal delay in forwarding the reports to the central office responsible for analysis, timely turn-round in processing the data returned, and intelligent analysis of the surveillance output. The action needed to investigate the causes of observed increases in reported malformations is not specifically under discussion in this paper, other than to say that there is a need to have procedures available for setting up retrospective inquiries to look into causal factors.
4.
a. Collection of Data The Area Medical Officer (AMO) collects information on each malformed child notified in his area, and forwards reports on standard forms, one form per child, to the OPCS monthly. The form1 provides details concerning the child (date and place of birth, birth-weight, sex, gestation, whether born alive or dead, all malformations detected) and age and parity of the mother. The malformations present are indicated on a check-list of 66 categories of malformations arranged in groups suitable forrecordingvisible or easily detectable malformations present at birth. In processing the data the 66 categories are further grouped to form 28 groups, some of which include babies with two or more malformations. Thus babies with both cleft lip and cleft palate and with either of these malformations are grouped into "babies with facial clefts". In 1974 in England and Wales, 98 area health authorities each provided monthly notifications of babies having one or more of 66 categories of malformations. With the addition of the 28 groups formed for processing, a total of more than 9000 comparisons are needed each month to check whether any of the categories of malformations have increased or decreased in any of the areas. Monthly tabulations are produced about 5-6 months after the babies were born, giving the numbers of each type of malformation and the numbers of babies with combined malformations, and these tables are sent as a return to AMOs. In order to investigate increases or decreases in the 9000 or so individual series of data, they are analysed with the aid of two types of statistical test. The results are printed only if they are significant at a prescribed level. In this way the volume of output from the computer is confined to a manageable level. b. Monitoring of Data Two types of statistical monitoring tests are used in the surveillance of the data. The first involves the calculation of an expected number of malformations for each class of abnormality and for each area. For a given class of malformations, the number of notifications in England and Wales in a particular month is computed. The appropriate fraction of this total, based on the ratio of the total births in the area to the total national births, is then assigned as the expected number of malformations in that area. This assumption is equivalent to postulating a uniform risk over the entire country for the month in question. The expected frequency is compared with the observed frequency of occurrence, and the standard normal deviation, z, is calculated: Observed—Expected z=VExpected This statistic, z, is calculated for each area and each class of malformation. For small areas and some categories of mal-
Monitoring in England and Wales
In the rest of this paper we discuss the monitoring system that has been in operation in England and Wales since 1964.
1 Copies of the form (Form SD56) ire available from The Director and Regtstnr General, Office of Population Caaastt and Sorwyt (C. M. Section), WlnjScld House, 316 Commercial Road, Pommouth, Hints, PO1 4TJ
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Josephine A. C. Weatherall &J. C. Haskey
SURVEILLANCE OF MALFORMATIONS FIG. I. Two examples of a Poisson distribution fitting monthly numbers of malformations a:} Heart and circulatory b: Reduction deformities: system malformations malformations In In Area B, 1947-71
The choice of the decision boundary raises some important considerations. It is desirable to detect any epidemic quickly and this implies that the decision boundary should be low. On the other hand, there should be as few false alarms as possible; this requires that the decision boundary should be high. A balance between these two opposing aims has been achieved in practice by choosing a decision boundary level so that, on average, 500 months pass before a false alarm is given, whereas only three months, on average, have to elapse before a true increase is detected. These two " average run lengths " have been arbitrarily chosen at the outset as being suitable for the malformation surveillance scheme. They apply to all the time-series under scrutiny. Each series of data requires its own reference value and decision boundary value. The reference value is determined by the level of reporting in years during which no epidemics were judged to have occurred. The decision boundary value is then obtained from a reference table (Ewan & Kemp, 1960) which ensures maximum sensitivity for detecting real changes with the average run lengths as chosen. The technique is applied monthly for each class of abnormality in each area, and significant results are printed out. The Poisson distribution is found to provide an adequate fit to the monthlyfiguresfor a large number of classes of malformations. Usually, these classes appear to have little associated seasonal variation and consist of those malformations which are easily identified. Examples are given in fig. 1. Reduction deformities are among the more easily detectable of malformations and the Poisson distributionfitsvery well, as indicated by the y} goodness-of-fit test (x 2 = 1-10, not significant at the 70% level, 3 degrees of freedom (d.f.)). Heart and circulatory malformations are perhaps less completely diagnosed, but the Poisson distribution adequately describes the observed variation (x 2= 5.16, not significant at the 30% level, 5d.f.). Figure 2a shows the time-series of monthly numbers of cleft lip cases in an administrative area having approximately 1200 total births per month. There seems to have been a dearth of cases in 1972 and possibly a large number in the first eight months of 1969. Figure 2b shows how the cusum confirms the clustering of cases. There were insufficient cases, however, to cause the cusum to exceed the decision boundary and so give a warning. In the absence of an epidemic, a Poisson distribution is found tofitthe data well (x2 = 2.44, not significant at the 60 % level, 4 d.f.) (fig. 2c). Figure 3a shows the corresponding figures for cleft palate cases in the same area. The Poisson distribution describes the variation well (x2 = 4.90, not significant at the 40 % level, 5 d.f.) (fig. 3c). There appears to be a succession of high frequencies for several months beginning in February 1974; and the plotted cusum (fig. 3b) exceeds the decision boundary in April, triggering the warning system. This illustrates the sensitivity of the method to runs of high values in the data. The cusum did not exceed the decision boundary when five cases were notified in September 1971. The cusum rose at this point, but insufficiently to give an alarm, because in both August and October only a single case was notified. After the significant rise in April 1974, fewer cases than usual were reported each month. This suggests that the "epidemic" was probably not due to an environmental agent, but to a clustering of cases in time. It is of interest that the method gives warning after the third consecutive high value. The mean level for this time-series of cleft palate cases is 1.131 cases per month (seefig.3c). This is estimated over the period 1967-73, when no epidemics are deemed to have occurred. Thereferencetables indicate that, for
AreaC, 1947-71
25 Momnty numb«f cri 0v« birth* and sUQbrths In Ajea B 1300
I 20 •3 15 ±
10
~l
Ob»«rv«d frequency Exptcted fiBouwwy lbas«d on flttwj Portaon distribution with p*/sjn«tirA-i 50)
Monthly n m t o at iv» birth* and stiltAThs hi ArosC3«00 Observed fn)qu«ncy Expectsti frequency (based on fjlsd Potsson distribution with p«r«mehw*-0e67) • 0 867 - 0 829
5
esses *i month
Josephine A. C. Weatherall &J. C. Haskey
cssm ri month
formations, the observed frequencies closely follow a Poisson distribution2 (see fig. 1), and z is Normally3 distributed with mean zero and unit variance. By printing out the names of the areas and types of malformation whose values of z are numerically greater than a "critical" value, particularly large departures from the average level may be distinguished. A critical value of 3.0 is used, and under the assumption of Normality, this corresponds to a two-tailed test with significance level of 0.27% (i.e., values greater than 3 for |z| are likely to occur by chance only about three times in a thousand tests). The scheme produces a warning, but shows only that the incidence of that malformation in that place is above or below the average of that malformation in England and Wales at that time. The second statistical surveillance scheme depends on the cumulative sum (cusum) technique. This technique, originally developed for quality control in industrial continuous production processes, provides the ability to detect quickly any shift in mean level of a series of data measurements. Both the current and previous data values are used in this method. For malformation surveillance, the numbers of notifications in successive months constitute the time-series data. Whilst a straightforward plotting of the data may indicate long-term trends and seasonal variation, it is difficult to detect by eye slight changes in mean level, and even harder to decide precisely when they occur. The cusum technique overcomes this problem by successively cumulating the values of the timeseries after first subtracting a value called the reference value, K. Once the cusum exceeds a critical value, known as the decision boundary value, H, the mean level is said to have changed. This makes the test particularly sensitive to runs in the series of very large or very small values. Should the mean level of reporting alter, there is a strong chance of observing several consecutive values above or below the previous mean level. If, however, the mean level remains constant, the possibility of a run of high or low values is much less likely. 2 The Poisson distribution is given by:
where: Pin) a the probability of n malformations occurring in a month, and X is the parameter of the Poisson distribution. The mean and variance of the distribution are equal and given by: n —A, variance ™ A > The capital letter N refers to observations whose statistical variation il describable by the Normal (Gaussian) Distribution Function.—ED.
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SURVEILLANCE OF MALFORMATIONS Josephine A. C. Weatherall &J. C. Haskey FIG. 2. Cleft lip in Area A at Monthly frequencies of deft lip cases Monthly number of live births and stillbirths in Area A 1200 4-
o
2-
z 0-
MILL b: Plot of cumulative sum
Decision boundary value, H - 5 Reference level, AC - 2
5-
1967
1968
1969
1970
Decision boundary
1971
1972
1973
1974
run lengths will be different from the values of 3 and 500, and the scheme will be less sensitive than supposed in discriminating between real epidemics and false ones. When the mean and variance of the monthly frequencies are approximately equal, the assumption of a Poisson distribution is usually justifiable. Often, however, the variance is larger than the mean. This may be the result of: (i) changes in the birth rate altering very slightly the mean of the series; (ii) changes due to seasonal components; (iii) spurious "epidemics" due to changes in efficiency of data collection; and (iv) different malformations, e.g. congenital dislocation of the hip, talipes and malformations of external genitalia, being diagnosed with varying degrees of certainty. Increase in uncertainty in diagnosis leads to greater variability in the data. A distribution which is found to fit many of the malformation time-series well is that of the negative binomial, which is defined by two parameters, r and p (as opposed to the one, X, for the Poisson): prq*
P(*) = ( - l
= 0, 1,2,...
I 3 FIG. 3. Cleft palate in Area A
2
a: Monthly frequencies of cleft palate cases
1•
0-
1967
1968
1969
1970
1971
1972
1973
Monthly number of live births and stillbirths In Area A 1200 Epidemic
1974
ct Distribution of monthly numbers of deft lip cases, 1967-73 40-
Observed frequency Expected frequency (based on fitted Poisson distribution with parameterX-1.1786)
10
I BO-
Mean -1.1786 Variance -1.281
'S 20-
1
10
1967
1
2
1968
1969
1970
1971
1972
1973
1974
3
b: Plot of cumulative sum
Number of i in month
Decision boundary value, H - 5 Reference level, K-2
the average run lengths chosen, values of H = 5 and K = 2 are appropriate for this mean. Using these values, it is therefore to be expected that any clustering of cases will cause an alert at about the third month. Returning to fig. 2a, no epidemics occurred in a period of 93 months. A chance run of high numbers, causing a false epidemic warning, would be expected only about once every 500 months, i.e., only once in 40 years. A period of eight years without an epidemic is therefore not surprising. There are several reasons for supposing that the Poisson distribution should describe the variation in the data in non-epidemic periods. The Poisson model assumes that malformations occur randomly through time and that the number of cases in one month does not influence the number of cases in other months. Also, the chance of a malformation occurring in a short interval of time is assumed to depend directly on the length of the interval. For the chosen average run lengths, the reference table values of Hand K depend on the assumption that the monthly frequencies follow a Poisson distribution. This is not true for all types of malformation. If the reference and decision boundary values are chosen on the false assumption of a Poisson distribution, then the effective
11
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1969
1970
1971
1972
1973
1974
Distribution of monthly ily numbers numb of deft palate cases, 1967-73 Observed frequency Expected frequency (based on fitted Poisson distribution with parameter A-1.131) Mean-1.131 Variance-1.080 2 3 Number of cases In month
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1968
Decision boundary
SURVEILLANCE OF MALFORMATIONS Josephine A. C. Weatherall &J. C. Haskey FIG. 4. Two examples of a negative binomial distribution fitting monthly numbers of malformations (data for 114 months: July 1964December 1973) a: The Down syndrome (mongollsm) in Area D
I 30-
Observed frequency Expected frequency (baaed on fated neaathm blnomtaj distribution with parameter* r-5, 0-07971)
20
100-
In this paper we hope to have demonstrated how surveillance of congenital malformations notified at the time of birth can provide data of use to persons responsible for health care. The data have also been of value in other ways. The increased reporting of congenital malformations, which followed the campaign conducted by the Department of Health and Social Security to teach midwives to diagnose congenital dislocation of the hip, was reassuring both to that Department and to the persons responsible for monitoring. From time to time the suspected teratogenic effect of some factor in the environment has been examined and it has been possible to investigate relations between the occurrence of malformations and the occurrence of the suspected agent (e.g. malformations in areas where fluorides have been added to drinking-water). The notified number of children born alive with spina bifida has been used to estimate the number surviving by subtracting those known, from death-certificates, to have died. These estimates are of importance in planning for future services for disabled children. Finally, a random sample of the babies notified has been used in a follow-up study. The drugs prescribed for their mothers in early pregnancy have been compared with drugs prescribed to mothers of normal babies. So far, this study has yielded a significant association between pregnancy diagnosis tests and a subsequent malformed child (Greenberg, Inman, Weatherall & Adelstein, 1975) and more associations may become apparent when the data are analysed further. There are some potential uses of the data which at present are not exploited in England and Wales. The data could form the basis of a register of malformed children, particularly for children with malformations that have health care implications.
Monthly number o* Uve births and atflbttha m Area E 400
40 -Observed frequency Expected (mouency 1 based on frttad neuatrve blnomtaj distribution with parameter* 1 30 r-4. p-08714)
20
5. Further Uses of Data
b: Congenital dislocation of the hip In Area E
Monthly nurtwr ot Irve birth* and atJBWrths k\ Area D 000
n
have been employed. This should give the new scheme slightly greater sensitivity in detecting epidemics.
Maan - 0 67D2 Variance - 0 6643 2 3 4 5 Number at cases In month
Uaan - 1 2018 Variance - 1 5078 12
3 4 6 6 7
where: P(k) is the probability of k malformations occurring in a month, r is an integer, and q= 1 — p. The mean and variance of this distribution are, respectively,
-'.By P P2 suitable choice of the two parameters, r and p, the mean and variance may take any value independently of the other, in contrast to the Poisson situation. Examples of the distribution fitting data for cases of the Down syndrome and of congenital dislocation of the hip are shown in fig. 4. Both distributions fit well, as indicated by the y} statistics (fig. 4a, x2 = 0-49, not significant at the 95 % level, 4d.f.; fig. 4b, y}= 6.42, not significant at the 40% level, 7d.f.). Since the negative binomial is moreflexiblethan the Poisson distribution in describing variation in the data it has been incorporated into a remodelled cusum surveillance scheme, and the appropriate reference levels, calculated by I. D. Hill4 (personal communication),
* Table* are available from Dr I. D. Hill, MRC Division of Medical Computing, Clinical Research Centre, Northwick Park Hospital, Watford Road, Harrow, Middlesex, HA 1 3UJ
REFERENCES
Charles, E. (1951) Br. J. Soc. Med. 5, 41-61 Ewan, W. D. & Kemp, K. W. (1960) Biometrika, 47, 363-380 Gillman, J., Gilbert, C , Gillman, T. & Spence, I. (1948) S. Afr.
Nelson, M. M. (1957) Pediatrics, 19, 764-776 Registrar-General (1929) The Registrar-General's statistical review ofEnglandand Wales, for theyear 1927. Pt m : Text, pp. 128-131. HMSO, London Registrar General (1962) The Registrar General's statistical review of England and Wales for the year 1960. Pt HI: Commentary, pp. 67-68. HMSO, London Registrar-General for Scotland (1944) Eighty-fifth annual report of the Registrar-General for Scotland, 1939, p. xiv. HMSO, Edinburgh Smithells, R. W. (1962) Dev. Med. ChildNeurol. 4,320-324 Weatherall, J. A. C. (1969) Med. Off-121,65-68 Wilson, J. G. (1957) Pediatrics, 19, 755-763 Winberg, J. (1964) Sven. Laekartidn. 61,722-741
J. Med. Sd. 13,47-90
Greenberg, G., Inman, W. H. W., Weatherall, J. A. C. & Adelstein, A. M. (1975) Br. Med. J. 2,191-192 [Letter] Gregg, N. M. (1941) Trans. Ophthalmol. Soc. Aust. 3, 35-45 HaskTn, D. (1948) Anat. Rec. 102,493-511 Hill, G. B., Spicer, C. C. & Weatherall, J. A. C. (1968) Br. Med. Bull. 24,215-218 Kallen, B. & Winberg, J. (1969) Pediatrics, 44,410-417 Klemetti, A. & Saxen, L. (1970) The Finnish register of congenital malformations. Health Services Research of the National Board of Health in Finland, Helsinki
44
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Br. Med, BuSL 1976
be concerned with early detection of possible environmental hazards. Only in the last 50 years has the identification of malformed children been seen to be of importance. Although stillbirths were registered in England and Wales from 1927 (RegistrarGeneral, 1929) no causes were recorded until 1960 (Registrar General, 1962). Stillbirths and their causes were registered in Scotland from 1939 (Registrar-General for Scotland, 1944) and studies in the United Kingdom based on the incidence of anencephaly in all births have, until 1960, been based on Scottish births. The number of children who die because of malformations, however, gives no measure of the incidence of malformations present in children, since some malformations are compatible with life. Other malformations predispose children to an increased risk of death unless the condition is treated; and as effective methods of treatment are developed the numbers of children who die diminish (e.g. those with congenital heart disease and spina bifida). Schemes for counting all malformed children have existed in Birmingham since 1949, covering about 20000 births/year (Charles, 1951), and in Liverpool and Bootle since 1959 (about 9000 births/year) (Smithells, 1962). Neither of these schemes involved large enough numbers of births to allow the detection of a change either in frequency over a short period of time or in occurrence of very rare types of malformations. Even a national scheme in Sweden covering 20000-40000 births/year, begun in 1955, did not reveal the thalidomide epidemic at the time, although, in retrospect, increases in the occurrence of limb malformations were detectable during that period (Winberg, 1964).
SURVEILLANCE OF MALFORMATIONS JOSEPHINE A. C. WEATHERALL M.B. Ch.B. B.Sc. M.F.C.M. J. C. HASKEY M.Sc. Office of Population Censuses and Surveys, London 1 2 3 4
Surveillance systems Definitions used in the surveillance of malformations Data processing and monitoring Monitoring in England and Wales a Collection of data b Monitoring of data 5 Further uses of data References
Surveillance and monitoring are often used as though they are synonymous terms. "Surveillance" is defined in The shorter
Oxford English dictionary (SOED) as a "watch or guard kept over . . . a suspected person . . . or the like" and in the Concise Oxford dictionary, more succinctly, as "supervision, close observation or invigilation ". The verb " to monitor " is perhaps 50 years old when used in this context. It was introduced in the field of regulating recorded sound (SOED, 3rd ed., Addenda) and is now used for indicating regular measurements of any continuous process, particularly in situations where some action will be taken following a change. The two terms, surveillance and monitoring, have come to be closely interdependent when used to refer to a programme dealing with problems such as human malformations. In developed countries the nearly ninefold reduction in infant mortality achieved in the last 100 years has left congenital malformations as the largest single cause of infant loss, and attention in public health and medical research has turned towards the prevention of malformations. Between 1920 and 1940, research into the causation of malformation of mammalian offspring turned from genetic factors towards the components of the maternal diet, and the influence of vitamins was investigated (Nelson, 1957; Wilson, 1957). The first clear demonstration, however, that an environmental factor was causally implicated occurred when Gregg (1941) showed that rubella infection of the mother during pregnancy was associated with specific malformations in the subsequently born children. Further evidence about specific factors in the maternal environment was shown in animals by Haskin (1948) with nitrogen mustard and by Gillman, Gilbert, Gillman & Spence (1948) with trypan blue. But these and laterfindingsin animals did not alert toxicologists to the possible occurrence of similar events in human beings until, between 1958 and 1962, an epidemic of babies born with gross limb malformations was shown to be associated with the consumption of thalidomide by the mothers during pregnancy. Since then, awareness that environmental factors can cause abnormalities in babies has influenced persons responsible for health care to
1. Surveillance Systems Since the tragedy of the thalidomide epidemic, two needs have become apparent: first to be on the alert for new factors in the environment that may cause malformations, and secondly to know the persons in a community whose malformations lead them to require special help. These challenges have spurred the development of three main types of information system. One type involves the detailed prospective recording of events and medication during pregnancy for every birth in a given population, so that malformations can be related to events during pregnancy. Such information schemes have been tried in special studies but data collection and analysis are costly. With conditions such as major malformations of the central nervous system (CNS) about 300 normal births have to be recorded in order to find one baby with a defect of this type, even in countries where these defects are common. In countries with all births in hospital and with adequate routine recording of antenatal procedures and medication, the recorded data can be extremely valuable when examinedretrospectivelyfor malformed infants and for control babies (Kallen & Winberg, 1969; Klemetti & Saxen, 1970). Some prospective studies, such as those in West Germany, parts of Scotland, England and Wales and parts of France, have concentrated on collecting information about medicines administered during pregnancy; but the largest of these studies includes only about 15000 births and they lack information about the weeks before women register their pregnancies. A second type of information system involves registering, at birth only, the babies born with malformations to measure the prevalence at birth. Such schemes have been established in England and Wales, Northern Ireland, some parts of the USA, 39
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Josephine A. C. Weatherall&J. C. Haskey
SURVEILLANCE OF MALFORMATIONS
Josephine A. C. Weatherall&J. C. Haskey another medical officer. Alternatively both medical officers may notify the case, giving rise to double recording. Although complete and reliable recording of malformations at birth could be obtained by utilizing multiple sources of information, such as hospital records, midwives' records, local health department records and by re-examining every reported child to confirm the diagnosis, a quicker and less expensive reporting system which accepts unvalidated diagnoses can provide a flow of information which will allow changes in occurrence of malformations to be recognized. The data should be interpreted with reservation; some malformations will be under-reported, some notified with scrupulous care and some over-reported; nevertheless, the variations in reporting can be detected and their significance analysed. Artefacts resulting from the method of reporting are likely to be confined to particular hospitals or areas, whereas environmental factors are not likely to be confined within administrative boundaries.
most provinces of Canada, and recently in many countries which have adopted a statutory medical certificate at birth (e.g. Belgium, France and Denmark). Several countries record all congenital defects, no matter at what age they are discovered, as is done in British Columbia. This sort of system depends on the maintenance of a register of identified persons so that reports from several sources can be collated and a true count of affected persons obtained. This type of information system is essential in order to make estimates of prevalence of malformations which are not obvious at birth and which cause little or no ill health or handicap. The true estimate of many types of malformation cannot be made until all the affected persons have had a reasonable chance of their malformation being found and registered. This system of registration can, however, be used to provide estimates of the prevalence of malformations in the population at any given age. To detect quickly environmental influences that cause malformations it is desirable to analyse the recorded data at frequent intervals, beginning as soon as possible after birth. Most of the schemes for registering malformations at birth have been set up to achieve this end. However, the schemes for recording all cases, detected at any age, have an important complementary role in informing genetic counsellors about the risks of malformed children being born either to persons known themselves to have had malformations or to those who belong to families with affected individuals.
3.
Data Processing and Monitoring
A scheme for notification of malformations, established as an early warning system, must be processed quickly. The system will reflect changes in the efficiencies of reporting and will therefore, unless reporting is validated, not provide a reliable "source" of data for studying epidemiological characteristics. The frequency of analysis of the data and the geographical areas chosen will depend on the total numbers of births involved. Ideally, the birth denominators should be available at the time of analysis, so that incidence rates can be calculated. However where this is not possible, there is no reason why the reported number of malformations should not be examined as a series by themselves, without regard to the denominator. The groupings of malformations used for counting are of great importance. "All reported malformations" is a somewhat complicated category, since one baby may be reported with several different malformations and other babies with only one; in this way the over-all total reflects the thoroughness with which multiple malformations are recorded. Similarly, the figure for "total babies with malformations" is likely to be influenced by the individual reporting officer's concept of what constitutes a malformation, and is likely to vary from area to area. By considering particular types of well-defined malformations in individual areas these disadvantages are minimized. Well-defined categories of malformations, such as babies with cleft palate only, babies with cleft lip only, and babies with both defects, are grouped so that all babies with facial clefts can be counted. Similarly, the well-defined CNS malformations are counted separately and grouped to form the class of all babies with CNS disorders. It is desirable to study the data periodically to find which malformations occur in groups more frequently than by chance, and these non-randomly associated malformations can be used to form new classes for monitoring; and study of them may suggest some new causal factors. The ratio of the rates of serious malformations to all malformations, and the ratio of specific malformations to all malformations, and many other such ratios, may provide useful information about the methods of recording and help in interpreting any observed changes. Although malformation categories are grouped for some purposes into broad classes, such as "all limb defects" or "all disorders of the alimentary tract", it is useful to retain the ability to analyse the exact constituent malformations. Increases in groups formed from congenital dislocation of the
2. Definitions Used in the Surveillance of Malformations In setting up any scheme for counting events, clear definitions of these events are essential. In the field of vital statistics, an event as seemingly precise as a birth may depend on the gestational age or weight of the child and vary in legal definition from country to country. Since malformations themselves are probably a cause of miscarriage or of premature delivery, the precise period of gestation needs to be stipulated. The definitions of a live birth vary, too, and in countries where legal registration takes place only for children alive at some given time after birth the population denominator of live births may need to be corrected if valid comparisons are to be made with countries where the taking of a single breath operates as the criterion of a live birth. Within a given country, however, definitions remain constant and a watch may be kept on the numbers of malformed children being born. Factors such as the thoroughness of post-mortem examinations, especially of stillborn children, will affect the numbers detected and the apparent frequencies of the malformations. The malformations themselves are not always clearly defined. Gross hydrocephaly or anencephaly will not be missed but congenital dislocation of the hip, mongolism, or internal malformations may well go unrecognized unless specially looked for. As several malformations may occur in the same baby it is desirable to allow each to be reported, so that groups of associated malformations may be studied. Both rubella and thalidomide produced characteristic groupings of malformations and the appearance of a new grouping may be thefirstsign of a new teratogenic substance in the environment. Apart from difficulties with definitions and diagnosis there are potential difficulties in the transmission of information both within a hospital and within the system for collecting the data. The local medical officer responsible for recording data in the area of a mother's residence may fail to hear about the birth of her malformed infant in a hospital within the area of 40
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SURVEILLANCE OF MALFORMATIONS
The methods used have not substantially altered since they were described by Hill, Spicer & Weatherall (1968) and by Weatherall (1969). With the reorganization of the National Health Service and conversion of the General Register Office to the Office of Population Censuses and Surveys (OPCS), certain changes have been made. The following describes the statistical systems being used in 1975, and indicates the officers responsible for gathering the primary data.
hip, detection of which depends on the thoroughness with which the baby is examined and on the subjective judgement of the examiner, with the more objectively identifiable polydactyly, syndactyly, reduction deformities and talipes, should not be allowed to cause undue alarm until the reasons for the variation in numbers have been determined. The interpretation of variations in the data sometimes presents difficulties, but an observed increase acts as a stimulus to examine the data more thoroughly to decide whether or not an epidemic has occurred. Any simple monitoring system, such as a chart showing the numbers reported, can be used for surveillance, whilst moresensitive tests can be devised by statisticians to help distinguish true changes due to some external factor from changes due to chance. Such analyses should be both by reporting area and by geographical area, so that increases and decreases due to artefacts in the methods of reporting can be identified quickly. They may thus be distinguished from the more serious possibilities of real epidemic increases. The choice of the methods used in monitoring depends on the type and quantity of the data available. When data are collected, as in England and Wales, in each of a large number of small areas, and for many distinct classes of malformations within each area, an automated computer-based scheme presents the most efficient way of surveillance of the incoming data. Although routine tabulations of the data are produced, the computer is used to perform routine statistical tests to detect increases and decreases, and only the statistically significant results are reported. An appropriate model is needed to describe the statistical distribution of the monthly numbers of malformations and once this is identified reliable statistical tests may be chosen. Malformations that occur relatively frequently, such as anencephaly and talipes, with approximate incidence rates of 1300 and 3800 per million total births, respectively, provide incidence rates of several cases per month in a typical area; this is large enough to permit quick detection of changes in the mean level. Some of the important malformations, however, are quite rare, e.g. anophthalmos and microphthalmos; and to detect such malformations, which occur at a rate of about 40 per million total births, it is generally necessary to observe the occurrence in much larger groups, in order that a true change in the incidence of the malformation may be revealed. Such large groups of births can be obtained only by aggregating births from wide geographical areas occurring at a specific time, or by analysing data collected over long time-periods. The essential factors for a monitoring system are, therefore: consistency in the recording of events, minimal delay in forwarding the reports to the central office responsible for analysis, timely turn-round in processing the data returned, and intelligent analysis of the surveillance output. The action needed to investigate the causes of observed increases in reported malformations is not specifically under discussion in this paper, other than to say that there is a need to have procedures available for setting up retrospective inquiries to look into causal factors.
4.
a. Collection of Data The Area Medical Officer (AMO) collects information on each malformed child notified in his area, and forwards reports on standard forms, one form per child, to the OPCS monthly. The form1 provides details concerning the child (date and place of birth, birth-weight, sex, gestation, whether born alive or dead, all malformations detected) and age and parity of the mother. The malformations present are indicated on a check-list of 66 categories of malformations arranged in groups suitable forrecordingvisible or easily detectable malformations present at birth. In processing the data the 66 categories are further grouped to form 28 groups, some of which include babies with two or more malformations. Thus babies with both cleft lip and cleft palate and with either of these malformations are grouped into "babies with facial clefts". In 1974 in England and Wales, 98 area health authorities each provided monthly notifications of babies having one or more of 66 categories of malformations. With the addition of the 28 groups formed for processing, a total of more than 9000 comparisons are needed each month to check whether any of the categories of malformations have increased or decreased in any of the areas. Monthly tabulations are produced about 5-6 months after the babies were born, giving the numbers of each type of malformation and the numbers of babies with combined malformations, and these tables are sent as a return to AMOs. In order to investigate increases or decreases in the 9000 or so individual series of data, they are analysed with the aid of two types of statistical test. The results are printed only if they are significant at a prescribed level. In this way the volume of output from the computer is confined to a manageable level. b. Monitoring of Data Two types of statistical monitoring tests are used in the surveillance of the data. The first involves the calculation of an expected number of malformations for each class of abnormality and for each area. For a given class of malformations, the number of notifications in England and Wales in a particular month is computed. The appropriate fraction of this total, based on the ratio of the total births in the area to the total national births, is then assigned as the expected number of malformations in that area. This assumption is equivalent to postulating a uniform risk over the entire country for the month in question. The expected frequency is compared with the observed frequency of occurrence, and the standard normal deviation, z, is calculated: Observed—Expected z=VExpected This statistic, z, is calculated for each area and each class of malformation. For small areas and some categories of mal-
Monitoring in England and Wales
In the rest of this paper we discuss the monitoring system that has been in operation in England and Wales since 1964.
1 Copies of the form (Form SD56) ire available from The Director and Regtstnr General, Office of Population Caaastt and Sorwyt (C. M. Section), WlnjScld House, 316 Commercial Road, Pommouth, Hints, PO1 4TJ
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Josephine A. C. Weatherall &J. C. Haskey
SURVEILLANCE OF MALFORMATIONS FIG. I. Two examples of a Poisson distribution fitting monthly numbers of malformations a:} Heart and circulatory b: Reduction deformities: system malformations malformations In In Area B, 1947-71
The choice of the decision boundary raises some important considerations. It is desirable to detect any epidemic quickly and this implies that the decision boundary should be low. On the other hand, there should be as few false alarms as possible; this requires that the decision boundary should be high. A balance between these two opposing aims has been achieved in practice by choosing a decision boundary level so that, on average, 500 months pass before a false alarm is given, whereas only three months, on average, have to elapse before a true increase is detected. These two " average run lengths " have been arbitrarily chosen at the outset as being suitable for the malformation surveillance scheme. They apply to all the time-series under scrutiny. Each series of data requires its own reference value and decision boundary value. The reference value is determined by the level of reporting in years during which no epidemics were judged to have occurred. The decision boundary value is then obtained from a reference table (Ewan & Kemp, 1960) which ensures maximum sensitivity for detecting real changes with the average run lengths as chosen. The technique is applied monthly for each class of abnormality in each area, and significant results are printed out. The Poisson distribution is found to provide an adequate fit to the monthlyfiguresfor a large number of classes of malformations. Usually, these classes appear to have little associated seasonal variation and consist of those malformations which are easily identified. Examples are given in fig. 1. Reduction deformities are among the more easily detectable of malformations and the Poisson distributionfitsvery well, as indicated by the y} goodness-of-fit test (x 2 = 1-10, not significant at the 70% level, 3 degrees of freedom (d.f.)). Heart and circulatory malformations are perhaps less completely diagnosed, but the Poisson distribution adequately describes the observed variation (x 2= 5.16, not significant at the 30% level, 5d.f.). Figure 2a shows the time-series of monthly numbers of cleft lip cases in an administrative area having approximately 1200 total births per month. There seems to have been a dearth of cases in 1972 and possibly a large number in the first eight months of 1969. Figure 2b shows how the cusum confirms the clustering of cases. There were insufficient cases, however, to cause the cusum to exceed the decision boundary and so give a warning. In the absence of an epidemic, a Poisson distribution is found tofitthe data well (x2 = 2.44, not significant at the 60 % level, 4 d.f.) (fig. 2c). Figure 3a shows the corresponding figures for cleft palate cases in the same area. The Poisson distribution describes the variation well (x2 = 4.90, not significant at the 40 % level, 5 d.f.) (fig. 3c). There appears to be a succession of high frequencies for several months beginning in February 1974; and the plotted cusum (fig. 3b) exceeds the decision boundary in April, triggering the warning system. This illustrates the sensitivity of the method to runs of high values in the data. The cusum did not exceed the decision boundary when five cases were notified in September 1971. The cusum rose at this point, but insufficiently to give an alarm, because in both August and October only a single case was notified. After the significant rise in April 1974, fewer cases than usual were reported each month. This suggests that the "epidemic" was probably not due to an environmental agent, but to a clustering of cases in time. It is of interest that the method gives warning after the third consecutive high value. The mean level for this time-series of cleft palate cases is 1.131 cases per month (seefig.3c). This is estimated over the period 1967-73, when no epidemics are deemed to have occurred. Thereferencetables indicate that, for
AreaC, 1947-71
25 Momnty numb«f cri 0v« birth* and sUQbrths In Ajea B 1300
I 20 •3 15 ±
10
~l
Ob»«rv«d frequency Exptcted fiBouwwy lbas«d on flttwj Portaon distribution with p*/sjn«tirA-i 50)
Monthly n m t o at iv» birth* and stiltAThs hi ArosC3«00 Observed fn)qu«ncy Expectsti frequency (based on fjlsd Potsson distribution with p«r«mehw*-0e67) • 0 867 - 0 829
5
esses *i month
Josephine A. C. Weatherall &J. C. Haskey
cssm ri month
formations, the observed frequencies closely follow a Poisson distribution2 (see fig. 1), and z is Normally3 distributed with mean zero and unit variance. By printing out the names of the areas and types of malformation whose values of z are numerically greater than a "critical" value, particularly large departures from the average level may be distinguished. A critical value of 3.0 is used, and under the assumption of Normality, this corresponds to a two-tailed test with significance level of 0.27% (i.e., values greater than 3 for |z| are likely to occur by chance only about three times in a thousand tests). The scheme produces a warning, but shows only that the incidence of that malformation in that place is above or below the average of that malformation in England and Wales at that time. The second statistical surveillance scheme depends on the cumulative sum (cusum) technique. This technique, originally developed for quality control in industrial continuous production processes, provides the ability to detect quickly any shift in mean level of a series of data measurements. Both the current and previous data values are used in this method. For malformation surveillance, the numbers of notifications in successive months constitute the time-series data. Whilst a straightforward plotting of the data may indicate long-term trends and seasonal variation, it is difficult to detect by eye slight changes in mean level, and even harder to decide precisely when they occur. The cusum technique overcomes this problem by successively cumulating the values of the timeseries after first subtracting a value called the reference value, K. Once the cusum exceeds a critical value, known as the decision boundary value, H, the mean level is said to have changed. This makes the test particularly sensitive to runs in the series of very large or very small values. Should the mean level of reporting alter, there is a strong chance of observing several consecutive values above or below the previous mean level. If, however, the mean level remains constant, the possibility of a run of high or low values is much less likely. 2 The Poisson distribution is given by:
where: Pin) a the probability of n malformations occurring in a month, and X is the parameter of the Poisson distribution. The mean and variance of the distribution are equal and given by: n —A, variance ™ A > The capital letter N refers to observations whose statistical variation il describable by the Normal (Gaussian) Distribution Function.—ED.
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SURVEILLANCE OF MALFORMATIONS Josephine A. C. Weatherall &J. C. Haskey FIG. 2. Cleft lip in Area A at Monthly frequencies of deft lip cases Monthly number of live births and stillbirths in Area A 1200 4-
o
2-
z 0-
MILL b: Plot of cumulative sum
Decision boundary value, H - 5 Reference level, AC - 2
5-
1967
1968
1969
1970
Decision boundary
1971
1972
1973
1974
run lengths will be different from the values of 3 and 500, and the scheme will be less sensitive than supposed in discriminating between real epidemics and false ones. When the mean and variance of the monthly frequencies are approximately equal, the assumption of a Poisson distribution is usually justifiable. Often, however, the variance is larger than the mean. This may be the result of: (i) changes in the birth rate altering very slightly the mean of the series; (ii) changes due to seasonal components; (iii) spurious "epidemics" due to changes in efficiency of data collection; and (iv) different malformations, e.g. congenital dislocation of the hip, talipes and malformations of external genitalia, being diagnosed with varying degrees of certainty. Increase in uncertainty in diagnosis leads to greater variability in the data. A distribution which is found to fit many of the malformation time-series well is that of the negative binomial, which is defined by two parameters, r and p (as opposed to the one, X, for the Poisson): prq*
P(*) = ( - l
= 0, 1,2,...
I 3 FIG. 3. Cleft palate in Area A
2
a: Monthly frequencies of cleft palate cases
1•
0-
1967
1968
1969
1970
1971
1972
1973
Monthly number of live births and stillbirths In Area A 1200 Epidemic
1974
ct Distribution of monthly numbers of deft lip cases, 1967-73 40-
Observed frequency Expected frequency (based on fitted Poisson distribution with parameterX-1.1786)
10
I BO-
Mean -1.1786 Variance -1.281
'S 20-
1
10
1967
1
2
1968
1969
1970
1971
1972
1973
1974
3
b: Plot of cumulative sum
Number of i in month
Decision boundary value, H - 5 Reference level, K-2
the average run lengths chosen, values of H = 5 and K = 2 are appropriate for this mean. Using these values, it is therefore to be expected that any clustering of cases will cause an alert at about the third month. Returning to fig. 2a, no epidemics occurred in a period of 93 months. A chance run of high numbers, causing a false epidemic warning, would be expected only about once every 500 months, i.e., only once in 40 years. A period of eight years without an epidemic is therefore not surprising. There are several reasons for supposing that the Poisson distribution should describe the variation in the data in non-epidemic periods. The Poisson model assumes that malformations occur randomly through time and that the number of cases in one month does not influence the number of cases in other months. Also, the chance of a malformation occurring in a short interval of time is assumed to depend directly on the length of the interval. For the chosen average run lengths, the reference table values of Hand K depend on the assumption that the monthly frequencies follow a Poisson distribution. This is not true for all types of malformation. If the reference and decision boundary values are chosen on the false assumption of a Poisson distribution, then the effective
11
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1969
1970
1971
1972
1973
1974
Distribution of monthly ily numbers numb of deft palate cases, 1967-73 Observed frequency Expected frequency (based on fitted Poisson distribution with parameter A-1.131) Mean-1.131 Variance-1.080 2 3 Number of cases In month
43
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1968
Decision boundary
SURVEILLANCE OF MALFORMATIONS Josephine A. C. Weatherall &J. C. Haskey FIG. 4. Two examples of a negative binomial distribution fitting monthly numbers of malformations (data for 114 months: July 1964December 1973) a: The Down syndrome (mongollsm) in Area D
I 30-
Observed frequency Expected frequency (baaed on fated neaathm blnomtaj distribution with parameter* r-5, 0-07971)
20
100-
In this paper we hope to have demonstrated how surveillance of congenital malformations notified at the time of birth can provide data of use to persons responsible for health care. The data have also been of value in other ways. The increased reporting of congenital malformations, which followed the campaign conducted by the Department of Health and Social Security to teach midwives to diagnose congenital dislocation of the hip, was reassuring both to that Department and to the persons responsible for monitoring. From time to time the suspected teratogenic effect of some factor in the environment has been examined and it has been possible to investigate relations between the occurrence of malformations and the occurrence of the suspected agent (e.g. malformations in areas where fluorides have been added to drinking-water). The notified number of children born alive with spina bifida has been used to estimate the number surviving by subtracting those known, from death-certificates, to have died. These estimates are of importance in planning for future services for disabled children. Finally, a random sample of the babies notified has been used in a follow-up study. The drugs prescribed for their mothers in early pregnancy have been compared with drugs prescribed to mothers of normal babies. So far, this study has yielded a significant association between pregnancy diagnosis tests and a subsequent malformed child (Greenberg, Inman, Weatherall & Adelstein, 1975) and more associations may become apparent when the data are analysed further. There are some potential uses of the data which at present are not exploited in England and Wales. The data could form the basis of a register of malformed children, particularly for children with malformations that have health care implications.
Monthly number o* Uve births and atflbttha m Area E 400
40 -Observed frequency Expected (mouency 1 based on frttad neuatrve blnomtaj distribution with parameter* 1 30 r-4. p-08714)
20
5. Further Uses of Data
b: Congenital dislocation of the hip In Area E
Monthly nurtwr ot Irve birth* and atJBWrths k\ Area D 000
n
have been employed. This should give the new scheme slightly greater sensitivity in detecting epidemics.
Maan - 0 67D2 Variance - 0 6643 2 3 4 5 Number at cases In month
Uaan - 1 2018 Variance - 1 5078 12
3 4 6 6 7
where: P(k) is the probability of k malformations occurring in a month, r is an integer, and q= 1 — p. The mean and variance of this distribution are, respectively,
-'.By P P2 suitable choice of the two parameters, r and p, the mean and variance may take any value independently of the other, in contrast to the Poisson situation. Examples of the distribution fitting data for cases of the Down syndrome and of congenital dislocation of the hip are shown in fig. 4. Both distributions fit well, as indicated by the y} statistics (fig. 4a, x2 = 0-49, not significant at the 95 % level, 4d.f.; fig. 4b, y}= 6.42, not significant at the 40% level, 7d.f.). Since the negative binomial is moreflexiblethan the Poisson distribution in describing variation in the data it has been incorporated into a remodelled cusum surveillance scheme, and the appropriate reference levels, calculated by I. D. Hill4 (personal communication),
* Table* are available from Dr I. D. Hill, MRC Division of Medical Computing, Clinical Research Centre, Northwick Park Hospital, Watford Road, Harrow, Middlesex, HA 1 3UJ
REFERENCES
Charles, E. (1951) Br. J. Soc. Med. 5, 41-61 Ewan, W. D. & Kemp, K. W. (1960) Biometrika, 47, 363-380 Gillman, J., Gilbert, C , Gillman, T. & Spence, I. (1948) S. Afr.
Nelson, M. M. (1957) Pediatrics, 19, 764-776 Registrar-General (1929) The Registrar-General's statistical review ofEnglandand Wales, for theyear 1927. Pt m : Text, pp. 128-131. HMSO, London Registrar General (1962) The Registrar General's statistical review of England and Wales for the year 1960. Pt HI: Commentary, pp. 67-68. HMSO, London Registrar-General for Scotland (1944) Eighty-fifth annual report of the Registrar-General for Scotland, 1939, p. xiv. HMSO, Edinburgh Smithells, R. W. (1962) Dev. Med. ChildNeurol. 4,320-324 Weatherall, J. A. C. (1969) Med. Off-121,65-68 Wilson, J. G. (1957) Pediatrics, 19, 755-763 Winberg, J. (1964) Sven. Laekartidn. 61,722-741
J. Med. Sd. 13,47-90
Greenberg, G., Inman, W. H. W., Weatherall, J. A. C. & Adelstein, A. M. (1975) Br. Med. J. 2,191-192 [Letter] Gregg, N. M. (1941) Trans. Ophthalmol. Soc. Aust. 3, 35-45 HaskTn, D. (1948) Anat. Rec. 102,493-511 Hill, G. B., Spicer, C. C. & Weatherall, J. A. C. (1968) Br. Med. Bull. 24,215-218 Kallen, B. & Winberg, J. (1969) Pediatrics, 44,410-417 Klemetti, A. & Saxen, L. (1970) The Finnish register of congenital malformations. Health Services Research of the National Board of Health in Finland, Helsinki
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Br. Med, BuSL 1976
