IJC International Journal of Cancer
Risk factors for cancers of unknown primary site: Results from the prospective EPIC cohort €mer4,5, Heiner Boeing6, Elisabet Wirfa €lt7, Rudolf Kaaks1, Disorn Sookthai1, Kari Hemminki2,3, Alwin Kra 8,9,10,11 12 13 13 14,15 Elisabete Weiderpass , Kim Overvad , Anne Tjïnneland , Anja Olsen , Petra H. Peeters , n Quiro s21, H. Bas Bueno-de-Mesquita15,16,17, Salvatore Panico18, Valeria Pala19, Paolo Vineis15,20, J. Ramo 22,23 23,24 23,25 23,26 Sa nchez ~aga Eva Ardanaz , Marıa-Jose , Maria-Dolores Chirlaque , Nerea Larran , Paul Brennan27, 28,29,30 28,30 29,30,31 €ran Hallmans32, Kay-Tee Khaw33, Dimitrios Trichopoulos , Antonia Trichopoulou , Pagona Lagiou , Go 34 15 35 Timothy J. Key , Elio Riboli and Federico Canzian 1
Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany Division of Molecular Genetic Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany 3 €, Sweden Center for Primary Health Care Research, Lund University, Malmo 4 Clinical Cooperation Unit, Molecular Hematology and Oncology, German Cancer Research Center (DKFZ), Heidelberg, Germany 5 Department of Internal Medicine V, University of Heidelberg, Heidelberg, Germany 6 €cke, Nuthetal, Germany Department of Epidemiology, German Institute of Human Nutrition (DIfE) Potsdam-Rehbru 7 €, Sweden Department of Clinical Sciences, Lund University, Malmo 8 Department of Community Medicine, Faculty of Health Sciences, UiT The Arctic University of Norway, Tromsï, Norway 9 Department of Research, Cancer Registry of Norway, Oslo, Norway 10 Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden 11 Samfundet Folkh€alsan, Helsinki, Finland 12 Department of Public Health, Section for Epidemiology, Aarhus University, Aarhus, Denmark 13 Danish Cancer Society Research Center, Copenhagen, Denmark 14 Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center, Utrecht, The Netherlands 15 Department of Epidemiology and Biostatistics, School of Public Health, Imperial College, London, United Kingdom 16 National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands 17 Department of Gastroenterology and Hepatology, University Medical Centre, Utrecht, The Netherlands 18 Department of Clinical and Experimental Medicine, Federico II University, Naples, Italy 19 Department of Preventive & Predictive Medicine, Nutritional Epidemiology Unit, Fondazione IRCCS Istituto, Nazionale dei Tumori, Milan, Italy 20 Human Genetics Foundation (HuGeF), Torino, Italy 21 Public Health Directorate, Asturias, Spain 22 Navarre Public Health Institute, Pamplona, Spain 23 CIBER Epidemiology and Public Health CIBERESP, Spain 24 n Biosanitaria de Granada (Granada.ibs), Granada, Spain blica, Instituto de Investigacio Escuela Andaluza de Salud Pu 25 Department of Epidemiology, Murcia Regional Health Authority, Murcia, Spain 26 Public Health Division of Gipuzkoa, Department of Health of the regional Government of the Basque Country, San Sebastian, Spain
Key words: cancer of unknown primary site (CUP), prospective cohort study, smoking, alcohol, obesity, waist circumference Disclosure: The authors have declared no conflicts of interest. Grant sponsors: European Commission (DG-SANCO); International Agency for Research on Cancer, Danish Cancer Society (Denmark); Ligue contre le Cancer, Mutuelle Generale de l’Education Nationale, Institut National de la Sante et de la Recherche Medicale (France); Deutsche Krebshilfe, Deutsches Krebsforschungszentrum and Federal Ministry of Education and Research (Germany); Hellenic Health Foundation (Greece); Italian Association for Research on Cancer (AIRC) and National Research Council (Italy); Dutch Ministry of Public Health, Welfare and Sports (VWS), Netherlands Cancer Registry (NKR), LK Research Funds, Dutch Prevention Funds, Dutch ZON (Zorg Onderzoek Nederland), World Cancer Research Fund (WCRF), Statistics Netherlands (The Netherlands); Norwegian Research Council, Norwegian Cancer Society, Nordforsk, Nordic Centre of Excellence programme on Food, Nutrition and Health (Norway); Health Research Fund (FIS), Catalan Institute of Oncology, Swedish Cancer Society, Swedish Scientific Council and Regional Government of Skåne and V€asterbotten (Sweden); Cancer Research UK, Medical Research Council, Stroke Association; British Heart Foundation, Department of Health, Welcome Trust (United Kingdom); Grant sponsor: European Research Council; Grant number: ERC-2009-AdG 232997; Grant sponsor: Spanish Ministry of Health; Grant number: ISCIII RETICC RD06/0020/0091; Grant sponsor: Regional Governments of Andalucıa, Asturias, Basque Country, Murcia and Navarra; Grant number: ISCIII RETIC (RD06/0020; Spain); Grant sponsor: Deutsche Krebshilfe; Grant numbers: EU FP7/2007-2013, (260715) DOI: 10.1002/ijc.28874 History: Received 6 Dec 2013; Accepted 4 Mar 2014; Online 2 Apr 2014 Correspondence to: Rudolf Kaaks, Department of Cancer Epidemiology, German Cancer Research Center (DKFZ) Heidelberg, Im Neuenheimer Feld 581, D-69120 Heidelberg, Germany, Tel: 149 6221 42 22 19, Fax: 149 6221 42 22 03, E-mail: [email protected]
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Section of Genetics, International Agency for Research on Cancer (IARC), Lyon, France Hellenic Health Foundation, Athens, Greece 29 Department of Epidemiology, Harvard School of Public Health, Boston, MA 30 Bureau of Epidemiologic Research, Academy of Athens, Athens, Greece 31 Department of Hygiene, Epidemiology and Medical Statistics, WHO Collaborating Center for Food and Nutrition Policies, University of Athens Medical, Greece 32 Department of Public Health and Clinical Medicine/Nutritional Research, Umea˚ University, Umea˚, Sweden 33 School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom 34 Cancer Epidemiology Unit, Nuffield Department of Clinical Medicine, University of Oxford, United Kingdom 35 Genomic Epidemiology Group, German Cancer Research Center (DKFZ), Heidelberg, Germany 28
Cancer of unknown primary site (CUP) may be called an “orphan” disease, as it is diagnosed when metastases are detected while the primary tumor typically remains undetected, and because little research has been done on its primary causes. So far, few epidemiological studies, if any, have addressed possible risk factors for CUP. We analyzed data from the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort (N 5 476,940). During prospective follow-up, a total of 651 cases of incident cases of CUP were detected (ICD-O-2 code C809). Proportional hazards models were conducted to examine the associations of lifetime history of smoking habits, alcohol consumption, levels of education and anthropometric indices of adiposity with risk of being diagnosed with CUP. Risk of being diagnosed with CUP was strongly related to smoking, with a relative risk of 3.66 [95% C.I., 2.24–5.97] for current, heavy smokers (261 cigarettes/day) compared to never smokers (adjusted for alcohol consumption, body mass index, waist circumference and level of education) and a relative risk of 5.12 [3.09–8.47] for cases with CUP who died within 12 months. For alcohol consumption and level of education, weaker associations were observed but attenuated and no longer statistically significant after adjusting for smoking and indices of obesity. Finally, risk of CUP was increased by approximately 30 per cent for subjects in the highest versus lowest quartiles of waist circumference. Our analyses provide further documentation, in addition to autopsy studies, that a substantial proportion of cancers of unknown primary site may have their origin in smoking-related tumors, in particular.
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What’s new? When cancer appears as metastatic disease but no primary tumor can be observed, it’s called “cancer of unknown primary site.” Little is known about the risk factors for this type of cancer. This study analyzed data from a European cohort and discovered a strong association between smoking and these cancers. Other risk factors they identified were drinking alcohol and being fat. This is the first epidemiological study of these type of cancers, and it strengthens the observations from autopsy studies that many of these cancers of unknown primary site stem from smoking-related tumors.
Cancer of unknown primary site (CUP) has been called an “orphan” disease because it is diagnosed when one or more metastases are detected while the primary tumor typically remains undetected.1 It accounts for about 3–5% of cancer occurrences overall, but generally has a highly aggressive clinical course associated with very short (pre-)clinical history and short survival times, and ranks fourth to fifth among causes of cancer deaths.2,3 Autopsy studies could identify primary tumors in about 50–75% of cases with CUP, and showed that the lung, liver, pancreas and gastrointestinal tract (esophagus, colorectum) are common sites for primary tumors.1 Histologically, CUP includes essentially adenocarcinomas (40–60%), and undifferentiated carcinomas (30%), and a small remaining proportion of poorly differentiated tumors, squamous cell carcinomas and small cell carcinomas. The predominant theory regarding CUP is that it may represent a family of tumor forms that
form metastases more rapidly than usual tumors at the same organ site of origin, and that these metastases have a stronger than usual growth potential in comparison to the primary tumor. A parallel theory is that the primary tumors giving rise to CUP have a reduced growth, or even regress, for example as a result of immune suppression. A recent study within the Swedish Family-Cancer Database demonstrated familial clustering of CUP and the association of CUP with occurrence of many other cancers, in large part tumors originating from organs suspected to be responsible for many CUP diagnoses such as cancers of the lung, colorectum and liver, but also tumors of the ovary and kidney.4 The latter results suggest that the primary tumor types underlying CUP might share some common genetic predisposition factors. A further reason why CUP is appropriately called an “orphan” disease is that comparatively little basic research has been done on its primary causes. Hardly anything is C 2014 UICC Int. J. Cancer: 00, 00–00 (2014) V
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Material and Methods Study population
The EPIC study is an ongoing multicenter population-based cohort study to investigate the relation between diet, nutritional and metabolic characteristics, lifestyle factors, and subsequent cancer incidence and cause specific mortality. The cohort consists of 521,448 participants (367,993 women and 153,455 men), enrolled into the cohort between 1992 and 2000, in 23 study centers across 10 different countries (i.e. Denmark, France, Germany, Greece, Italy, the Netherlands, Norway, Spain, Sweden and United Kingdom). At recruitment, the majority of participants were aged between 35 and 70 years7 with the noticeable exception of a subcohort in the United Kingdom, which included individuals in the age range of 45–74 (EPIC-Norfolk, Cambridge) and 20–97 years (health conscious subcohort, Oxford; http://epic.iarc.fr/centers/uk. php). Detailed information about the selection of the studypopulation, data collection and follow-up procedures have been reported previously.7 All participants of the EPIC cohort gave written informed consent, and the study was approved by the International Agency for Research on Cancer ethical review committee and by the local committees at the participating centers. At baseline, questionnaires and computer-guided, face-toface interviews were used to collect information about basic demographic variables, past illnesses, use of medications and lifestyle. Questionnaire information on lifestyle covered lifetime history as well as current habits (at the time of recruitment) of smoking and alcohol consumption, and detailed questions on diet and physical activity. Baseline physical examinations included measurements of height, weight and waist circumferences following standardized procedures. Although weight and height were available for all participants, only 77.55% of participants had waist circumference measurements. A total of 44,508 participants who had reported a prevalent or previous cancer at the time of baseline recruitment or who had no follow-up data were excluded, leaving a total of 476,940 cohort participants for the present analyses. C 2014 UICC Int. J. Cancer: 00, 00–00 (2014) V
Prospective ascertainment of incident cancer cases and vital status; coding of cancer endpoints
In all countries except France, Germany, Greece and Naples (Italy) incident cancer cases are identified using record linkage with cancer and pathology registries. In France, cancer occurrence is prospectively ascertained through linkages with health insurance records, and in Germany and Greece through regular direct contacts with participants and their next of kin. In all of the three latter countries, self-reported disease occurrences are systematically verified against clinical and pathological records and coded by specialized study physicians. Information on vital status is collected from regional or national mortality registries. Cancer incidence data are coded according to the International Classification of Diseases for Oncology (ICD-O-2), and mortality data are coded according to the 10th Revision of the International Statistical Classification of Diseases, Injuries and Causes of Death (ICD-10). The latest updates of endpoint data for cancer incidence and vital status were between 2005 and 2010, depending on the study center. Up to this latest update, a total of 1050 cancer endpoints were identified with the ICD-O-2 code (C809) for CUP. Of these 1050, 318 additionally had morphology codes for lymphoma (N 5 141), skin cancers (N 5 32) or other/miscellaneous histology N 5 145), and these were excluded from the analyses. Furthermore, as 80 of all 81 cases of CUP in France had missing morphology status, the French subcohort was excluded entirely from the present analyses. Thus, after excluding a total of 399 subjects amongst cases coded C809, a core set of 651 tumors of primary origin remained, which had morphology codes indicating the tumor was an adenocarcinoma (N 5 273), a carcinoma (N 5 140), malignant neoplasm (N 5 210), or other codes for diverse, undifferentiated tumors (N 5 28) and these formed the set of tumors of unknown primary origin retained for our present analyses. For 522 of the 651 cases of CUP in this core set additional information on 12-month survival was available.
Statistical analyses
Proportional hazards models were used to estimate relative risks (hazard ratios and their 95% confidence intervals) of CUP by levels of body mass index (BMI), waist circumference, alcohol consumption, education and smoking. Attained age was used as the underlying time scale and the time of origin of the study was age at recruitment, and study participants were considered at risk from their age at recruitment until the age at which either CUP was diagnosed or censoring was applied because of the occurrence of death, diagnosis of another type of cancer, loss to follow up or closure of the latest follow-up assessment. The proportional hazards assumption was checked by examining time-by-covariate interaction terms to test whether the hazard ratio was constant over time, no strong violation of this assumption were noted. Participants were divided into quartile categories of BMI and waist circumference with gender specific quartile cut-
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known about epidemiological risk factors for CUP. A study of Swedish cancer registry data has shown roughly equal incidence rates for CUP among men and women, and a slowly increasing time trend to about years 1995–2000, followed by a sharp decline of about 25%.2 The authors could only speculate, however, about the reasons for these temporal incidence patterns. The few epidemiologic reports so far that addressed possible risk factors showed an increased risk of CUP among low socioeconomic population groups5 and in relation to occupations linked with tobacco exposures.6 In the present article, we report the associations of three basic lifestyle-related risk factors—smoking, alcohol consumption, obesity and level of education–with risk of CUP within the European Prospective Investigation into Cancer and Nutrition “EPIC” cohort.
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Table 1. Characteristics of CUP cases by country and gender Survival time
Histological Subtypes
Country
Total
12 months (%)
Italy
37
24 (64.9)
13 (35.1)
Spain
36
27 (75.0)
9 (25.0)
21 (58.3)
7 (19.4)
5 (13.9)
3 (8.3)
1.3
United Kingdom
213
192 (90.1)
21 (9.9)
50 (23.5)
68 (31.9)
92 (43.2)
3 (1.4)
3.3
The Netherlands
53
41 (77.4)
12 (22.6)
37 (69.8)
3 (5.7)
8 (15.1)
5 (9.4)
1.7
Greece
16
15 (93.8)
1 (6.3)
4 (25.0)
–
12 (75.0)
–
1.5
Germany
30
19 (63.3)
11 (36.7)
17 (56.7)
2 (6.7)
8 (26.7)
3 (10.0)
0.7
Sweden
125
97 (77.6)
28 (22.4)
44 (35.2)
23 (18.4)
53 (42.4)
5 (4.0)
1.9
Denmark
127
101 (79.5)
26 (20.5)
69 (54.3)
27 (21.3)
24 (18.9)
7 (5.5)
1.8
Norway
14
6 (42.9)
8 (57.1)
10 (71.4)
1 (7.1)
1 (7.1)
2 (14.3)
0.6
Male
266
229 (86.1)
37 (13.9)
105 (39.4)
54 (20.2)
97 (36.4)
11 (4.0)
1.8
Female
385
293 (76.1)
92 (23.9)
168 (43.6)
86 (22.4)
113 (29.5)
17 (4.5)
1.4
651
522 (80.2)
129(19.8)
273 (41.9)
140 (21.5)
210 (32.3)
28 (4.3)
1.5
> 12 months (%)
Adenocarcinoma (%)
Carcinoma (%)
Neoplasm (%)
Other (%)
CUP as proportion of all cancer occurrences (%)
21 (56.8)
9 (24.3)
7 (18.9)
–
1.0
Gender
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points based on the full study cohort. With regard to smoking-related variables, study participants were categorized according to smoking status at the time of recruitment (never, past, current). Subjects who reported current or past smoking at baseline were further categorized by lifetime average number of cigarettes smoked per day (1–15, 16–25, 261), and past smokers were also further categorized by time since quitting (10 years). Categories of lifetime alcohol included lifetime nonconsumers (0 g/day), former consumers and current consumers (at the time of recruitment) drinking an average of >0–12, >12–24, >24–60 and >60 g/day. Levels of formal education were categorized into primary school or less, technical and professional school, secondary school and longer education including university. Univariate models, to assess the effects of single risk factors at a time, were stratified only for study center, sex and age at recruitment in 2-year categories. Trend tests across levels of exposure were assessed using continuous covariates. In addition, in multivariable models the associations of risk with lifetime smoking history and intensity, alcohol consumption habits, anthropometric indices of adiposity and levels of education were estimated with additional, mutual adjustments between these risk factor variables. Tests for interaction between risk factors were done by adding the multiplicative terms (cross-product term) in the model. Finally, sensitivity analyses were conducted to explore whether risk factors differed for CUP cases with survival times of up to 12 months (N 5 522).
Results An overview of the 651 incident cases of CUP by the nine countries retained for this analysis is in Table 1. The vast
majority of the CUP cases were coded as adenocarcinomas not otherwise specified (N 5 273) neoplasm not otherwise specified (N 5 210), or carcinoma not otherwise specified (N 5 140), and the remainder (labeled “other”) had morphology codes for mucinous/mucin-producing adenocarcinoma (N 5 16), signet ring cell carcinoma (N 5 7), solid carcinoma (N 5 2), small cell carcinoma (N 5 1) and tubular cell adenocarcinoma (N 5 2). The ratio of tumors coded adenocarcinomas to carcinomas not otherwise specified varied between the nine countries, from 0.74 to 12.33. CUP represented 1.5 per cent of the overall cancer occurrence, and this proportion varied from 0.7 to 3.3 per cent across the EPIC countries. Overall, the occurrence of CUP was roughly equal among men and women (rate ratio [RR] 5 1.13 [95% C.I. 5 0.88– 1.45]). The median age at diagnosis was 66.6 years (range 38.4–95.8 years). The median duration of survival after diagnosis, all countries combined, was 2 months (range 0–101 months), and of all 651 CUP cases, 522 (80%) had a survival time of less than 12 months (Table 1). The longest median survival time was noted in Norway and the shortest was in the United Kingdom and Greece. A higher level of formal education was associated with modest reduction in risk for CUP, although this inverse association was weakened after adjustments for smoking, alcohol consumption and adiposity (Table 1). Relative risks (RR) for CUP by level of major risk factors are presented in Table 2. Increased risks were observed among current smokers, with a relative risk of 4.05 [2.49– 6.58] (unadjusted model) (RR 5 3.66 [2.24–5.97], after additional adjustments for alcohol consumption, level of education, and adiposity) for current smokers of 261 cigarettes a C 2014 UICC Int. J. Cancer: 00, 00–00 (2014) V
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Table 2. Hazard ratios and 95% confidence intervals for CUP in relation to smoking, alcohol consumption, levels of education and anthropometric indices of obesity CUP with survival time 12 months
CUP No. of cases
Unadjusted1 HR (95%CI)
Adjusted1,2 HR (95%CI)
No. of cases
Unadjusted1 HR (95%CI)
Adjusted1,2 HR (95%CI)
Smoking intensity3 Never smoked
219
Referent
Referent
166
Referent
Referent
Current smokers, 1–15 cigarettes/ day
88
1.86 (1.44,2.40)
1.81 (1.39,2.34)
72
2.20 (1.65,2.93)
2.10 (1.57,2.80)
Current smokers, 16–25 cigarettes/ day
75
3.46 (2.63,4.56)
3.25 (2.46,4.30)
59
3.94 (2.88,5.39)
3.61 (2.63,4.95)
Current smokers, 261 cigarettes/ day
19
4.05 (2.49,6.58)
3.66 (2.24,5.97)
19
5.80 (3.53,9.54)
5.12 (3.09,8.47)
Former smokers, quit 10 years
58
1.39 (1.04,1.87)
1.34 (0.99,1.80)
47
1.53 (1.10,2.14)
1.46 (1.04,2.03)
Former smokers, quit >10 years
129
1.10 (0.88,1.38)
1.08 (0.86,1.36)
107
1.16 (0.90,1.50)
1.14 (0.88,1.47)
Current smokers, pipe or cigar
31
1.53 (1.02,2.28)
1.49 (1.00,2.23)
24
1.58 (1.00,2.48)
1.52 (0.97,2.40)
Former
54
1.19 (0.80,1.78)
1.05 (0.70,1.58)
47
1.34 (0.88,2.04)
1.17 (0.76,1.79)
0–12
292
Referent
Referent
235
Referent
Referent
>12–24
82
1.07 (0.83,1.39)
1.04 (0.80,1.35)
69
1.12 (0.84,1.49)
1.07 (0.81,1.43)
Average lifetime alcohol consumption (g/day)3
>24–60
66
1.42 (1.04,1.93)
1.26 (0.93,1.72)
59
1.57 (1.13,2.18)
1.37 (0.98,1.91)
>60
16
1.81 (1.02,3.23)
1.42 (0.79,2.53)
12
1.68 (0.88,3.24)
1.27 (0.66,2.45)
0.01
0.15
0.02
0.24
P
linear trend
Quartile1
144
Referent
Referent
123
Referent
Referent
Quartile2
152
0.90 (0.71,1.13)
0.92 (0.73,1.16)
122
0.85 (0.66,1.10)
0.88 (0.68,1.13)
Quartile3
169
0.96 (0.77,1.21)
0.98 (0.78,1.23)
128
0.86 (0.67,1.11)
0.88 (0.68,1.14)
Quartile4
169
1.04 (0.83,1.32)
1.06 (0.84,1.33)
140
1.03 (0.80,1.33)
1.04 (0.80,1.34)
0.35
0.29
0.58
0.52
P
linear trend
Waist circumference3 Quartile1
129
Referent
Referent
105
Referent
Referent
Quartile2
130
0.90 (0.70,1.16)
0.91 (0.71,1.16)
102
0.87 (0.66,1.15)
0.87 (0.66,1.15)
Quartile3
161
1.03 (0.81,1.31)
1.02 (0.80,1.30)
123
0.97 (0.74,1.27)
0.95 (0.73,1.25)
Quartile4
180
1.34 (1.06,1.71)
1.29 (1.02,1.65)
154
40 years versus
Risk factors for cancers of unknown primary site: Results from the prospective EPIC cohort €mer4,5, Heiner Boeing6, Elisabet Wirfa €lt7, Rudolf Kaaks1, Disorn Sookthai1, Kari Hemminki2,3, Alwin Kra 8,9,10,11 12 13 13 14,15 Elisabete Weiderpass , Kim Overvad , Anne Tjïnneland , Anja Olsen , Petra H. Peeters , n Quiro s21, H. Bas Bueno-de-Mesquita15,16,17, Salvatore Panico18, Valeria Pala19, Paolo Vineis15,20, J. Ramo 22,23 23,24 23,25 23,26 Sa nchez ~aga Eva Ardanaz , Marıa-Jose , Maria-Dolores Chirlaque , Nerea Larran , Paul Brennan27, 28,29,30 28,30 29,30,31 €ran Hallmans32, Kay-Tee Khaw33, Dimitrios Trichopoulos , Antonia Trichopoulou , Pagona Lagiou , Go 34 15 35 Timothy J. Key , Elio Riboli and Federico Canzian 1
Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany Division of Molecular Genetic Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany 3 €, Sweden Center for Primary Health Care Research, Lund University, Malmo 4 Clinical Cooperation Unit, Molecular Hematology and Oncology, German Cancer Research Center (DKFZ), Heidelberg, Germany 5 Department of Internal Medicine V, University of Heidelberg, Heidelberg, Germany 6 €cke, Nuthetal, Germany Department of Epidemiology, German Institute of Human Nutrition (DIfE) Potsdam-Rehbru 7 €, Sweden Department of Clinical Sciences, Lund University, Malmo 8 Department of Community Medicine, Faculty of Health Sciences, UiT The Arctic University of Norway, Tromsï, Norway 9 Department of Research, Cancer Registry of Norway, Oslo, Norway 10 Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden 11 Samfundet Folkh€alsan, Helsinki, Finland 12 Department of Public Health, Section for Epidemiology, Aarhus University, Aarhus, Denmark 13 Danish Cancer Society Research Center, Copenhagen, Denmark 14 Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center, Utrecht, The Netherlands 15 Department of Epidemiology and Biostatistics, School of Public Health, Imperial College, London, United Kingdom 16 National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands 17 Department of Gastroenterology and Hepatology, University Medical Centre, Utrecht, The Netherlands 18 Department of Clinical and Experimental Medicine, Federico II University, Naples, Italy 19 Department of Preventive & Predictive Medicine, Nutritional Epidemiology Unit, Fondazione IRCCS Istituto, Nazionale dei Tumori, Milan, Italy 20 Human Genetics Foundation (HuGeF), Torino, Italy 21 Public Health Directorate, Asturias, Spain 22 Navarre Public Health Institute, Pamplona, Spain 23 CIBER Epidemiology and Public Health CIBERESP, Spain 24 n Biosanitaria de Granada (Granada.ibs), Granada, Spain blica, Instituto de Investigacio Escuela Andaluza de Salud Pu 25 Department of Epidemiology, Murcia Regional Health Authority, Murcia, Spain 26 Public Health Division of Gipuzkoa, Department of Health of the regional Government of the Basque Country, San Sebastian, Spain
Key words: cancer of unknown primary site (CUP), prospective cohort study, smoking, alcohol, obesity, waist circumference Disclosure: The authors have declared no conflicts of interest. Grant sponsors: European Commission (DG-SANCO); International Agency for Research on Cancer, Danish Cancer Society (Denmark); Ligue contre le Cancer, Mutuelle Generale de l’Education Nationale, Institut National de la Sante et de la Recherche Medicale (France); Deutsche Krebshilfe, Deutsches Krebsforschungszentrum and Federal Ministry of Education and Research (Germany); Hellenic Health Foundation (Greece); Italian Association for Research on Cancer (AIRC) and National Research Council (Italy); Dutch Ministry of Public Health, Welfare and Sports (VWS), Netherlands Cancer Registry (NKR), LK Research Funds, Dutch Prevention Funds, Dutch ZON (Zorg Onderzoek Nederland), World Cancer Research Fund (WCRF), Statistics Netherlands (The Netherlands); Norwegian Research Council, Norwegian Cancer Society, Nordforsk, Nordic Centre of Excellence programme on Food, Nutrition and Health (Norway); Health Research Fund (FIS), Catalan Institute of Oncology, Swedish Cancer Society, Swedish Scientific Council and Regional Government of Skåne and V€asterbotten (Sweden); Cancer Research UK, Medical Research Council, Stroke Association; British Heart Foundation, Department of Health, Welcome Trust (United Kingdom); Grant sponsor: European Research Council; Grant number: ERC-2009-AdG 232997; Grant sponsor: Spanish Ministry of Health; Grant number: ISCIII RETICC RD06/0020/0091; Grant sponsor: Regional Governments of Andalucıa, Asturias, Basque Country, Murcia and Navarra; Grant number: ISCIII RETIC (RD06/0020; Spain); Grant sponsor: Deutsche Krebshilfe; Grant numbers: EU FP7/2007-2013, (260715) DOI: 10.1002/ijc.28874 History: Received 6 Dec 2013; Accepted 4 Mar 2014; Online 2 Apr 2014 Correspondence to: Rudolf Kaaks, Department of Cancer Epidemiology, German Cancer Research Center (DKFZ) Heidelberg, Im Neuenheimer Feld 581, D-69120 Heidelberg, Germany, Tel: 149 6221 42 22 19, Fax: 149 6221 42 22 03, E-mail: [email protected]
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Section of Genetics, International Agency for Research on Cancer (IARC), Lyon, France Hellenic Health Foundation, Athens, Greece 29 Department of Epidemiology, Harvard School of Public Health, Boston, MA 30 Bureau of Epidemiologic Research, Academy of Athens, Athens, Greece 31 Department of Hygiene, Epidemiology and Medical Statistics, WHO Collaborating Center for Food and Nutrition Policies, University of Athens Medical, Greece 32 Department of Public Health and Clinical Medicine/Nutritional Research, Umea˚ University, Umea˚, Sweden 33 School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom 34 Cancer Epidemiology Unit, Nuffield Department of Clinical Medicine, University of Oxford, United Kingdom 35 Genomic Epidemiology Group, German Cancer Research Center (DKFZ), Heidelberg, Germany 28
Cancer of unknown primary site (CUP) may be called an “orphan” disease, as it is diagnosed when metastases are detected while the primary tumor typically remains undetected, and because little research has been done on its primary causes. So far, few epidemiological studies, if any, have addressed possible risk factors for CUP. We analyzed data from the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort (N 5 476,940). During prospective follow-up, a total of 651 cases of incident cases of CUP were detected (ICD-O-2 code C809). Proportional hazards models were conducted to examine the associations of lifetime history of smoking habits, alcohol consumption, levels of education and anthropometric indices of adiposity with risk of being diagnosed with CUP. Risk of being diagnosed with CUP was strongly related to smoking, with a relative risk of 3.66 [95% C.I., 2.24–5.97] for current, heavy smokers (261 cigarettes/day) compared to never smokers (adjusted for alcohol consumption, body mass index, waist circumference and level of education) and a relative risk of 5.12 [3.09–8.47] for cases with CUP who died within 12 months. For alcohol consumption and level of education, weaker associations were observed but attenuated and no longer statistically significant after adjusting for smoking and indices of obesity. Finally, risk of CUP was increased by approximately 30 per cent for subjects in the highest versus lowest quartiles of waist circumference. Our analyses provide further documentation, in addition to autopsy studies, that a substantial proportion of cancers of unknown primary site may have their origin in smoking-related tumors, in particular.
Short Report
What’s new? When cancer appears as metastatic disease but no primary tumor can be observed, it’s called “cancer of unknown primary site.” Little is known about the risk factors for this type of cancer. This study analyzed data from a European cohort and discovered a strong association between smoking and these cancers. Other risk factors they identified were drinking alcohol and being fat. This is the first epidemiological study of these type of cancers, and it strengthens the observations from autopsy studies that many of these cancers of unknown primary site stem from smoking-related tumors.
Cancer of unknown primary site (CUP) has been called an “orphan” disease because it is diagnosed when one or more metastases are detected while the primary tumor typically remains undetected.1 It accounts for about 3–5% of cancer occurrences overall, but generally has a highly aggressive clinical course associated with very short (pre-)clinical history and short survival times, and ranks fourth to fifth among causes of cancer deaths.2,3 Autopsy studies could identify primary tumors in about 50–75% of cases with CUP, and showed that the lung, liver, pancreas and gastrointestinal tract (esophagus, colorectum) are common sites for primary tumors.1 Histologically, CUP includes essentially adenocarcinomas (40–60%), and undifferentiated carcinomas (30%), and a small remaining proportion of poorly differentiated tumors, squamous cell carcinomas and small cell carcinomas. The predominant theory regarding CUP is that it may represent a family of tumor forms that
form metastases more rapidly than usual tumors at the same organ site of origin, and that these metastases have a stronger than usual growth potential in comparison to the primary tumor. A parallel theory is that the primary tumors giving rise to CUP have a reduced growth, or even regress, for example as a result of immune suppression. A recent study within the Swedish Family-Cancer Database demonstrated familial clustering of CUP and the association of CUP with occurrence of many other cancers, in large part tumors originating from organs suspected to be responsible for many CUP diagnoses such as cancers of the lung, colorectum and liver, but also tumors of the ovary and kidney.4 The latter results suggest that the primary tumor types underlying CUP might share some common genetic predisposition factors. A further reason why CUP is appropriately called an “orphan” disease is that comparatively little basic research has been done on its primary causes. Hardly anything is C 2014 UICC Int. J. Cancer: 00, 00–00 (2014) V
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Material and Methods Study population
The EPIC study is an ongoing multicenter population-based cohort study to investigate the relation between diet, nutritional and metabolic characteristics, lifestyle factors, and subsequent cancer incidence and cause specific mortality. The cohort consists of 521,448 participants (367,993 women and 153,455 men), enrolled into the cohort between 1992 and 2000, in 23 study centers across 10 different countries (i.e. Denmark, France, Germany, Greece, Italy, the Netherlands, Norway, Spain, Sweden and United Kingdom). At recruitment, the majority of participants were aged between 35 and 70 years7 with the noticeable exception of a subcohort in the United Kingdom, which included individuals in the age range of 45–74 (EPIC-Norfolk, Cambridge) and 20–97 years (health conscious subcohort, Oxford; http://epic.iarc.fr/centers/uk. php). Detailed information about the selection of the studypopulation, data collection and follow-up procedures have been reported previously.7 All participants of the EPIC cohort gave written informed consent, and the study was approved by the International Agency for Research on Cancer ethical review committee and by the local committees at the participating centers. At baseline, questionnaires and computer-guided, face-toface interviews were used to collect information about basic demographic variables, past illnesses, use of medications and lifestyle. Questionnaire information on lifestyle covered lifetime history as well as current habits (at the time of recruitment) of smoking and alcohol consumption, and detailed questions on diet and physical activity. Baseline physical examinations included measurements of height, weight and waist circumferences following standardized procedures. Although weight and height were available for all participants, only 77.55% of participants had waist circumference measurements. A total of 44,508 participants who had reported a prevalent or previous cancer at the time of baseline recruitment or who had no follow-up data were excluded, leaving a total of 476,940 cohort participants for the present analyses. C 2014 UICC Int. J. Cancer: 00, 00–00 (2014) V
Prospective ascertainment of incident cancer cases and vital status; coding of cancer endpoints
In all countries except France, Germany, Greece and Naples (Italy) incident cancer cases are identified using record linkage with cancer and pathology registries. In France, cancer occurrence is prospectively ascertained through linkages with health insurance records, and in Germany and Greece through regular direct contacts with participants and their next of kin. In all of the three latter countries, self-reported disease occurrences are systematically verified against clinical and pathological records and coded by specialized study physicians. Information on vital status is collected from regional or national mortality registries. Cancer incidence data are coded according to the International Classification of Diseases for Oncology (ICD-O-2), and mortality data are coded according to the 10th Revision of the International Statistical Classification of Diseases, Injuries and Causes of Death (ICD-10). The latest updates of endpoint data for cancer incidence and vital status were between 2005 and 2010, depending on the study center. Up to this latest update, a total of 1050 cancer endpoints were identified with the ICD-O-2 code (C809) for CUP. Of these 1050, 318 additionally had morphology codes for lymphoma (N 5 141), skin cancers (N 5 32) or other/miscellaneous histology N 5 145), and these were excluded from the analyses. Furthermore, as 80 of all 81 cases of CUP in France had missing morphology status, the French subcohort was excluded entirely from the present analyses. Thus, after excluding a total of 399 subjects amongst cases coded C809, a core set of 651 tumors of primary origin remained, which had morphology codes indicating the tumor was an adenocarcinoma (N 5 273), a carcinoma (N 5 140), malignant neoplasm (N 5 210), or other codes for diverse, undifferentiated tumors (N 5 28) and these formed the set of tumors of unknown primary origin retained for our present analyses. For 522 of the 651 cases of CUP in this core set additional information on 12-month survival was available.
Statistical analyses
Proportional hazards models were used to estimate relative risks (hazard ratios and their 95% confidence intervals) of CUP by levels of body mass index (BMI), waist circumference, alcohol consumption, education and smoking. Attained age was used as the underlying time scale and the time of origin of the study was age at recruitment, and study participants were considered at risk from their age at recruitment until the age at which either CUP was diagnosed or censoring was applied because of the occurrence of death, diagnosis of another type of cancer, loss to follow up or closure of the latest follow-up assessment. The proportional hazards assumption was checked by examining time-by-covariate interaction terms to test whether the hazard ratio was constant over time, no strong violation of this assumption were noted. Participants were divided into quartile categories of BMI and waist circumference with gender specific quartile cut-
Short Report
known about epidemiological risk factors for CUP. A study of Swedish cancer registry data has shown roughly equal incidence rates for CUP among men and women, and a slowly increasing time trend to about years 1995–2000, followed by a sharp decline of about 25%.2 The authors could only speculate, however, about the reasons for these temporal incidence patterns. The few epidemiologic reports so far that addressed possible risk factors showed an increased risk of CUP among low socioeconomic population groups5 and in relation to occupations linked with tobacco exposures.6 In the present article, we report the associations of three basic lifestyle-related risk factors—smoking, alcohol consumption, obesity and level of education–with risk of CUP within the European Prospective Investigation into Cancer and Nutrition “EPIC” cohort.
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Risk factors for cancers of unknown primary site
Table 1. Characteristics of CUP cases by country and gender Survival time
Histological Subtypes
Country
Total
12 months (%)
Italy
37
24 (64.9)
13 (35.1)
Spain
36
27 (75.0)
9 (25.0)
21 (58.3)
7 (19.4)
5 (13.9)
3 (8.3)
1.3
United Kingdom
213
192 (90.1)
21 (9.9)
50 (23.5)
68 (31.9)
92 (43.2)
3 (1.4)
3.3
The Netherlands
53
41 (77.4)
12 (22.6)
37 (69.8)
3 (5.7)
8 (15.1)
5 (9.4)
1.7
Greece
16
15 (93.8)
1 (6.3)
4 (25.0)
–
12 (75.0)
–
1.5
Germany
30
19 (63.3)
11 (36.7)
17 (56.7)
2 (6.7)
8 (26.7)
3 (10.0)
0.7
Sweden
125
97 (77.6)
28 (22.4)
44 (35.2)
23 (18.4)
53 (42.4)
5 (4.0)
1.9
Denmark
127
101 (79.5)
26 (20.5)
69 (54.3)
27 (21.3)
24 (18.9)
7 (5.5)
1.8
Norway
14
6 (42.9)
8 (57.1)
10 (71.4)
1 (7.1)
1 (7.1)
2 (14.3)
0.6
Male
266
229 (86.1)
37 (13.9)
105 (39.4)
54 (20.2)
97 (36.4)
11 (4.0)
1.8
Female
385
293 (76.1)
92 (23.9)
168 (43.6)
86 (22.4)
113 (29.5)
17 (4.5)
1.4
651
522 (80.2)
129(19.8)
273 (41.9)
140 (21.5)
210 (32.3)
28 (4.3)
1.5
> 12 months (%)
Adenocarcinoma (%)
Carcinoma (%)
Neoplasm (%)
Other (%)
CUP as proportion of all cancer occurrences (%)
21 (56.8)
9 (24.3)
7 (18.9)
–
1.0
Gender
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Total
points based on the full study cohort. With regard to smoking-related variables, study participants were categorized according to smoking status at the time of recruitment (never, past, current). Subjects who reported current or past smoking at baseline were further categorized by lifetime average number of cigarettes smoked per day (1–15, 16–25, 261), and past smokers were also further categorized by time since quitting (10 years). Categories of lifetime alcohol included lifetime nonconsumers (0 g/day), former consumers and current consumers (at the time of recruitment) drinking an average of >0–12, >12–24, >24–60 and >60 g/day. Levels of formal education were categorized into primary school or less, technical and professional school, secondary school and longer education including university. Univariate models, to assess the effects of single risk factors at a time, were stratified only for study center, sex and age at recruitment in 2-year categories. Trend tests across levels of exposure were assessed using continuous covariates. In addition, in multivariable models the associations of risk with lifetime smoking history and intensity, alcohol consumption habits, anthropometric indices of adiposity and levels of education were estimated with additional, mutual adjustments between these risk factor variables. Tests for interaction between risk factors were done by adding the multiplicative terms (cross-product term) in the model. Finally, sensitivity analyses were conducted to explore whether risk factors differed for CUP cases with survival times of up to 12 months (N 5 522).
Results An overview of the 651 incident cases of CUP by the nine countries retained for this analysis is in Table 1. The vast
majority of the CUP cases were coded as adenocarcinomas not otherwise specified (N 5 273) neoplasm not otherwise specified (N 5 210), or carcinoma not otherwise specified (N 5 140), and the remainder (labeled “other”) had morphology codes for mucinous/mucin-producing adenocarcinoma (N 5 16), signet ring cell carcinoma (N 5 7), solid carcinoma (N 5 2), small cell carcinoma (N 5 1) and tubular cell adenocarcinoma (N 5 2). The ratio of tumors coded adenocarcinomas to carcinomas not otherwise specified varied between the nine countries, from 0.74 to 12.33. CUP represented 1.5 per cent of the overall cancer occurrence, and this proportion varied from 0.7 to 3.3 per cent across the EPIC countries. Overall, the occurrence of CUP was roughly equal among men and women (rate ratio [RR] 5 1.13 [95% C.I. 5 0.88– 1.45]). The median age at diagnosis was 66.6 years (range 38.4–95.8 years). The median duration of survival after diagnosis, all countries combined, was 2 months (range 0–101 months), and of all 651 CUP cases, 522 (80%) had a survival time of less than 12 months (Table 1). The longest median survival time was noted in Norway and the shortest was in the United Kingdom and Greece. A higher level of formal education was associated with modest reduction in risk for CUP, although this inverse association was weakened after adjustments for smoking, alcohol consumption and adiposity (Table 1). Relative risks (RR) for CUP by level of major risk factors are presented in Table 2. Increased risks were observed among current smokers, with a relative risk of 4.05 [2.49– 6.58] (unadjusted model) (RR 5 3.66 [2.24–5.97], after additional adjustments for alcohol consumption, level of education, and adiposity) for current smokers of 261 cigarettes a C 2014 UICC Int. J. Cancer: 00, 00–00 (2014) V
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Table 2. Hazard ratios and 95% confidence intervals for CUP in relation to smoking, alcohol consumption, levels of education and anthropometric indices of obesity CUP with survival time 12 months
CUP No. of cases
Unadjusted1 HR (95%CI)
Adjusted1,2 HR (95%CI)
No. of cases
Unadjusted1 HR (95%CI)
Adjusted1,2 HR (95%CI)
Smoking intensity3 Never smoked
219
Referent
Referent
166
Referent
Referent
Current smokers, 1–15 cigarettes/ day
88
1.86 (1.44,2.40)
1.81 (1.39,2.34)
72
2.20 (1.65,2.93)
2.10 (1.57,2.80)
Current smokers, 16–25 cigarettes/ day
75
3.46 (2.63,4.56)
3.25 (2.46,4.30)
59
3.94 (2.88,5.39)
3.61 (2.63,4.95)
Current smokers, 261 cigarettes/ day
19
4.05 (2.49,6.58)
3.66 (2.24,5.97)
19
5.80 (3.53,9.54)
5.12 (3.09,8.47)
Former smokers, quit 10 years
58
1.39 (1.04,1.87)
1.34 (0.99,1.80)
47
1.53 (1.10,2.14)
1.46 (1.04,2.03)
Former smokers, quit >10 years
129
1.10 (0.88,1.38)
1.08 (0.86,1.36)
107
1.16 (0.90,1.50)
1.14 (0.88,1.47)
Current smokers, pipe or cigar
31
1.53 (1.02,2.28)
1.49 (1.00,2.23)
24
1.58 (1.00,2.48)
1.52 (0.97,2.40)
Former
54
1.19 (0.80,1.78)
1.05 (0.70,1.58)
47
1.34 (0.88,2.04)
1.17 (0.76,1.79)
0–12
292
Referent
Referent
235
Referent
Referent
>12–24
82
1.07 (0.83,1.39)
1.04 (0.80,1.35)
69
1.12 (0.84,1.49)
1.07 (0.81,1.43)
Average lifetime alcohol consumption (g/day)3
>24–60
66
1.42 (1.04,1.93)
1.26 (0.93,1.72)
59
1.57 (1.13,2.18)
1.37 (0.98,1.91)
>60
16
1.81 (1.02,3.23)
1.42 (0.79,2.53)
12
1.68 (0.88,3.24)
1.27 (0.66,2.45)
0.01
0.15
0.02
0.24
P
linear trend
Quartile1
144
Referent
Referent
123
Referent
Referent
Quartile2
152
0.90 (0.71,1.13)
0.92 (0.73,1.16)
122
0.85 (0.66,1.10)
0.88 (0.68,1.13)
Quartile3
169
0.96 (0.77,1.21)
0.98 (0.78,1.23)
128
0.86 (0.67,1.11)
0.88 (0.68,1.14)
Quartile4
169
1.04 (0.83,1.32)
1.06 (0.84,1.33)
140
1.03 (0.80,1.33)
1.04 (0.80,1.34)
0.35
0.29
0.58
0.52
P
linear trend
Waist circumference3 Quartile1
129
Referent
Referent
105
Referent
Referent
Quartile2
130
0.90 (0.70,1.16)
0.91 (0.71,1.16)
102
0.87 (0.66,1.15)
0.87 (0.66,1.15)
Quartile3
161
1.03 (0.81,1.31)
1.02 (0.80,1.30)
123
0.97 (0.74,1.27)
0.95 (0.73,1.25)
Quartile4
180
1.34 (1.06,1.71)
1.29 (1.02,1.65)
154
40 years versus
