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Influence of diabetes mellitus on mortality in breast cancer patients Yunhai Zhou, Xiang Zhang, Chen Gu and Jiazeng Xia Department of General Surgery and Translational Medicine Center, Nanjing Medical University Affiliated Wuxi Second Hospital, Wuxi, China
Key words breast cancer, diabetes mellitus, diagnosis, mortality. Correspondence Dr Jiazeng Xia, Department of General Surgery and Translational Medicine Center, Nanjing Medical University Affiliated Wuxi Second Hospital, Wuxi 214002, China. Email: [email protected] Y. Zhou MD; X. Zhang MD; C. Gu MD; J. Xia MD. Accepted for publication 2 September 2014. doi: 10.1111/ans.12877
Abstract Background: Breast cancer is one of the most common malignant tumours among women worldwide. Besides, diabetes mellitus is also a major health problem in developed countries. This study explores the association between diabetes mellitus and breast cancer patients’ survival outcomes. Methods: A systematic literature search in Embase (http://www.embase.com) and MEDLINE (http://www.ncbi.nlm.nih.gov/pubmed) was conducted from January 1960 to April 2014 and systematically identified clinical studies that evaluated the association between breast cancer mortality and diabetes mellitus. Clinical studies investigating the association between diabetes mellitus and breast cancer patients’ survival outcomes were included. Results: Twenty publications were chosen for the meta-analysis, of which 16 studies had all-cause mortality data and 12 studies had breast cancer mortality data. Published from 2001 to 2013, all 20 studies followed a total of 2 645 249 patients including more than 207 832 diabetic patients. Pre-existing diabetes mellitus was associated with a 37% increased risk for all-cause mortality in women with breast cancer (hazard ratio (HR) = 1.37; 95% confidence interval (CI): 1.34–1.41; P = 0.02). Diabetes mellitus was associated with a 17% increased risk for breast cancer mortality in women with breast cancer (HR = 1.17; 95% CI: 1.11–1.22; P < 0.01). Conclusions: Women with diabetes mellitus are at higher risk of breast cancerspecific and all-cause mortality after initial breast cancer diagnosis.
Introduction Breast cancer is the leading neoplastic malignancy among women worldwide. It is the most commonly diagnosed non-skin cancer among US women, with more than 200 000 women diagnosed in 2010.1 Incidence rates are higher in Western countries than in Asia, but it was estimated that about half of the incident cases and 60% of the related deaths occurred in economically developing countries. Although the incidence and mortality rates of breast cancers are both decreasing in North America and some European countries, they have been increasing in Asian countries.2 Diabetes mellitus is currently among the most common life- and health-threatening chronic diseases. Diabetes mellitus and cancer are the major causes of morbidity and mortality worldwide. In the United States alone, by 2007, there were approximately 24 million people with diabetes mellitus (approximately 8% of the adult population) and 2.5 million survivors of breast cancer.3 Diabetes mellitus is a common endocrinopathy that has been shown to increase the incidence of multiple types of cancer, including breast cancer. ANZ J Surg 85 (2015) 972–978
Diabetes mellitus is also common among breast cancer patients. In a systematic review, 8–32% of breast cancer patients had diabetes mellitus,4 and breast cancer incidence may be higher among women with diabetes mellitus.5–7 The potential interactions between diabetes mellitus and breast cancer are not very clear and appear to be very complex. Less intensive care for either diabetes mellitus or breast cancer seems to negatively affect the survival in patients with diabetes mellitus and breast cancer.8 The aim of this study was to assess the association between diabetes mellitus and breast cancer patients’ survival outcomes.
Methods Selection of published studies We searched Embase (http://www.embase.com) and MEDLINE (http://www.ncbi.nlm.nih.gov/pubmed) from January 1960 to April 2014 and systematically identified clinical studies, which evaluated the association between breast cancer mortality and diabetes © 2014 Royal Australasian College of Surgeons
Influence of diabetes mellitus
973
mellitus. No language restriction was applied. Search terms included ‘diabetes mellitus’ or ‘insulin resistance’ or ‘hyperinsulinemia’ combined with ‘breast cancer’ or ‘breast neoplasm’ or ‘breast tumor’. The titles and abstracts of studies identified in the computerized search were scanned to exclude any article that was clearly irrelevant. The full text of the remaining articles was carefully read to determine whether it contained information on the topic of interest. We also scanned the cited references of retrieved articles to identify any additional relevant studies. Reference lists of review articles were also reviewed to check that the assembled list of relevant publications was complete.
the Universities of Newcastle, Australia, and Ottawa, Canada. It was primarily developed to assess the quality of non-randomized studies in the interpretation of meta-analytic results. The Newcastle–Ottawa scale develops a ‘star system’, whose goal is to provide an easy and convenient tool for quality assessment of nonrandomized studies to be used in a systematic review. Nonrandomized studies were judged on three broad perspectives as follows: the selection of study groups, comparability of groups and ascertainment of either the exposure or outcome of interest for prospective studies.
Data extraction and quality assessment
Statistical analysis
We independently evaluated the eligibility of all retrieved studies from the databases and extracted the relevant data from each included study using a unified data form. The items included in the data form were as follows: study name (together with the first author’s name and year of publication), journal name, location, study design, study population, inclusion criteria, exclusive criteria, range for follow-up and outcomes. The two lists from the authors were compared, and disagreements were resolved by consensus. Hazard ratio (HR) was recorded or calculated. If the study reported adjusted HRs, we prefer to extract-adjusted HRs into analysis. Otherwise, original HRs from raw data are included. The methodological quality of the included studies was assessed by means of the Newcastle–Ottawa scale for cohort studies.9 The Newcastle–Ottawa scale is an ongoing collaboration between
To compute a summary HR with its 95% confidence interval (CI), we used the study-specific most-adjusted HR and its 95% CI in all analyses. Publication bias was assessed via visual inspection of the funnel plots created by plotting the HR to standard error (SE) ([HR]) for included studies. We examined between-study heterogeneity using Cochran’s Q and I2 statistics. The I2 assess the percentage of variability in the effect estimates that is due to heterogeneity rather than chance. Fixed-effect model was presented if the P-value for heterogeneity was 50%. Otherwise, we would use the random effects model. We transformed the HR to a natural log scale and then calculated the SEs. The analysis was performed using STATA 12.0 software (StataCorp LP, College Station, TX, USA).
Fig. 1. Study selection diagram.
© 2014 Royal Australasian College of Surgeons
974
Zhou et al.
Results Literature search, study characteristics and quality assessment Figure 1 illustrates our search and selection process. The titles and abstracts of the primary 915 publications identified were reviewed and 834 were discarded after title and abstract review for one of the following reasons: they were not about cancer, they were not clinical studies or they were not human studies. Fifty more publications were also discarded after further evaluation for one of the following reasons: they were not about breast cancer, they did not evaluate the risk of diabetes mellitus, they did not evaluate prognostic outcomes or they did not apply to research question. Bibliographies were also searched for publications not identified in our database searches and
five more additional publications were found. The full text of total 36 articles was read through carefully. If the prognostic outcomes did not include mortality rate or no comparison was made between diabetic patients and non-diabetic patients, the publications were excluded. Finally, 20 publications were chosen for the meta-analysis,10–29 of which 16 studies10–17,20,22–25,27–29 had all-cause mortality data and 12 studies13,17–21,23–26,28,29 had breast cancer mortality data. The baseline characteristics of the studies included were summarized in Table 1. Published from 2001 to 2013, all 20 studies followed a total of 2 645 249 patients including more than 207 832 diabetic patients. Study-specific quality scores are summarized in Table 2. The range of quality scores was from 6 to 9. The median scores of included studies were 7.
Table 1 Characteristics of included studies Study
Year
No. of patients with DM
Total no.
Yancik
2001
NR
1800
Coughlin
2004
26 186
588 321
Du Tammemagi
2005 2005
73 127
588 906
Jee van de Poll-Franse
2005 2007
41 868 754
468 615 9725
Lipscombe
2008
1011
6107
Srokowski
2009
14 414
70 781
Zhou Seshasai
2010 2011
2103 40 116
44 655 820 900
Lam Irwin Schrauder
2011 2011 2011
23 560 58 276
367 361 604 4056
Liu
2011
1495
146 764
Yeh
2012
599
18 280
Redaniel
2012
52 657
82 867
Cleveland
2012
121
1447
Griffiths
2012
1784
2418
Chen
2012
341
4390
Nechuta
2013
289
4664
Age (years)
55–64 (35%) 65–74 (35%) >75 (31%) DM: mean, 61 NG: mean, 56 Mean 59 80 (9%) 49.6 DM: mean, 70.7 NG: mean, 58.9 DM: mean, 69.1 NG: mean, 68.0 66–70 (25%) 71–75 (27%) 76–80 (23%) 80+ (25%) 53.4 ± 9.5 DM: mean, 58 NG: mean, 55 48 58 DM: mean, 67.41 NG: mean, 56.85 DM: mean, 67 NG: mean, 60 DM: mean, 61.8 NG: mean, 51.5 70 (25.71%) DM: mean, 63.6 NG: mean, 57.4 DM: mean, 77.8 NG: mean, 77.7 DM: mean, 62.7 NG: mean, 53.0 20–75
Follow-up
Outcomes
30 months
All-cause mortality
16 years
All-cause mortality
3.68 years 10 (0.04–17.8) years
All-cause mortality All-cause mortality
10 years 3–10 years
Breast cancer mortality All-cause mortality
5 (0–10.9) years
All-cause mortality
2–12 years
All-cause mortality, breast cancer mortality
15.8 (9.1–23.2) years 13.6 years
Breast cancer mortality Breast cancer mortality
4 years 6 years 5 years
Breast cancer mortality All-cause mortality, breast cancer mortality All-cause mortality
7 years
Breast cancer mortality
17 years
All-cause mortality, breast cancer mortality
NR
All-cause mortality
96.4 (2.7–113.0) months
All-cause mortality, breast cancer mortality
NR
All-cause mortality, breast cancer mortality
67.2 months
All-cause mortality, breast cancer mortality
5.3 (0.64–8.9) years
All-cause mortality, breast cancer mortality
DM, diabetes mellitus; NG, normal glucose; NR, not reported.
© 2014 Royal Australasian College of Surgeons
Influence of diabetes mellitus
975
Table 2 Methodologic quality of cohort studies included in the meta-analysis Cohort studies
Year
Representativeness of the exposed cohort
Selection of the unexposed cohort
Yancik Coughlin Du Tammemagi Jee van de Poll-Franse Lipscombe Srokowski Zhou Seshasai Lam Irwin Schrauder Liu Yeh Redaniel Cleveland Griffiths Chen Nechuta
2001 2004 2005 2005 2005 2007
☆ ☆ ☆ ☆ ☆ ☆
☆ ☆ ☆ ☆ ☆ ☆
2008 2009 2010 2011 2011 2011 2011 2011 2012 2012 2012 2012 2012 2013
☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆
☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆
Ascertainment of exposure
☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆
Outcome of interest not present at start of study
Control for important factor or additional factor†
Outcome assessment
☆ ☆ ☆ ☆ ☆ ☆
☆ ☆☆ ☆☆ ☆☆ ☆☆ ☆☆
☆ ☆ ☆ ☆
☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆
☆☆ ☆☆ ☆☆ ☆☆ ☆☆ ☆☆ ☆☆ ☆☆ ☆☆ ☆☆ ☆☆ ☆☆ ☆☆ ☆☆
Follow-up long enough for outcomes to occur‡
☆ ☆ ☆ ☆ ☆ ☆
Adequacy of follow-up of cohorts§
Total quality scores
☆
☆ ☆
☆ ☆
☆ ☆
6 9 7 9 8 7
☆ ☆
☆ ☆
☆
☆
☆ ☆ ☆
☆
6 7 8 9 7 8 6 6 8 6 8 7 7 6
†A maximum of two stars could be awarded for this item. Studies that controlled for age received one star, whereas studies that controlled for other important confounders such as body mass index, smoking, family history of prostate cancer and so on received an additional star. ‡A cohort study with a follow-up time ≥8 years was assigned one star. §A cohort study with a follow-up rate >90% was assigned one star.
Table 3 Summary risk estimates of the association between diabetes mellitus and mortality of breast cancer patients Study
All-cause mortality Breast cancer mortality
16 12
HR (95% CI)
1.37 (1.34–1.41) 1.17 (1.11–1.22)
Egger’s test
0.021 0.509
Begg’s test
0.620 0.669
Heterogeneity test Q
P
I 2 (%)
35.33 59.51
0.002
Influence of diabetes mellitus on mortality in breast cancer patients Yunhai Zhou, Xiang Zhang, Chen Gu and Jiazeng Xia Department of General Surgery and Translational Medicine Center, Nanjing Medical University Affiliated Wuxi Second Hospital, Wuxi, China
Key words breast cancer, diabetes mellitus, diagnosis, mortality. Correspondence Dr Jiazeng Xia, Department of General Surgery and Translational Medicine Center, Nanjing Medical University Affiliated Wuxi Second Hospital, Wuxi 214002, China. Email: [email protected] Y. Zhou MD; X. Zhang MD; C. Gu MD; J. Xia MD. Accepted for publication 2 September 2014. doi: 10.1111/ans.12877
Abstract Background: Breast cancer is one of the most common malignant tumours among women worldwide. Besides, diabetes mellitus is also a major health problem in developed countries. This study explores the association between diabetes mellitus and breast cancer patients’ survival outcomes. Methods: A systematic literature search in Embase (http://www.embase.com) and MEDLINE (http://www.ncbi.nlm.nih.gov/pubmed) was conducted from January 1960 to April 2014 and systematically identified clinical studies that evaluated the association between breast cancer mortality and diabetes mellitus. Clinical studies investigating the association between diabetes mellitus and breast cancer patients’ survival outcomes were included. Results: Twenty publications were chosen for the meta-analysis, of which 16 studies had all-cause mortality data and 12 studies had breast cancer mortality data. Published from 2001 to 2013, all 20 studies followed a total of 2 645 249 patients including more than 207 832 diabetic patients. Pre-existing diabetes mellitus was associated with a 37% increased risk for all-cause mortality in women with breast cancer (hazard ratio (HR) = 1.37; 95% confidence interval (CI): 1.34–1.41; P = 0.02). Diabetes mellitus was associated with a 17% increased risk for breast cancer mortality in women with breast cancer (HR = 1.17; 95% CI: 1.11–1.22; P < 0.01). Conclusions: Women with diabetes mellitus are at higher risk of breast cancerspecific and all-cause mortality after initial breast cancer diagnosis.
Introduction Breast cancer is the leading neoplastic malignancy among women worldwide. It is the most commonly diagnosed non-skin cancer among US women, with more than 200 000 women diagnosed in 2010.1 Incidence rates are higher in Western countries than in Asia, but it was estimated that about half of the incident cases and 60% of the related deaths occurred in economically developing countries. Although the incidence and mortality rates of breast cancers are both decreasing in North America and some European countries, they have been increasing in Asian countries.2 Diabetes mellitus is currently among the most common life- and health-threatening chronic diseases. Diabetes mellitus and cancer are the major causes of morbidity and mortality worldwide. In the United States alone, by 2007, there were approximately 24 million people with diabetes mellitus (approximately 8% of the adult population) and 2.5 million survivors of breast cancer.3 Diabetes mellitus is a common endocrinopathy that has been shown to increase the incidence of multiple types of cancer, including breast cancer. ANZ J Surg 85 (2015) 972–978
Diabetes mellitus is also common among breast cancer patients. In a systematic review, 8–32% of breast cancer patients had diabetes mellitus,4 and breast cancer incidence may be higher among women with diabetes mellitus.5–7 The potential interactions between diabetes mellitus and breast cancer are not very clear and appear to be very complex. Less intensive care for either diabetes mellitus or breast cancer seems to negatively affect the survival in patients with diabetes mellitus and breast cancer.8 The aim of this study was to assess the association between diabetes mellitus and breast cancer patients’ survival outcomes.
Methods Selection of published studies We searched Embase (http://www.embase.com) and MEDLINE (http://www.ncbi.nlm.nih.gov/pubmed) from January 1960 to April 2014 and systematically identified clinical studies, which evaluated the association between breast cancer mortality and diabetes © 2014 Royal Australasian College of Surgeons
Influence of diabetes mellitus
973
mellitus. No language restriction was applied. Search terms included ‘diabetes mellitus’ or ‘insulin resistance’ or ‘hyperinsulinemia’ combined with ‘breast cancer’ or ‘breast neoplasm’ or ‘breast tumor’. The titles and abstracts of studies identified in the computerized search were scanned to exclude any article that was clearly irrelevant. The full text of the remaining articles was carefully read to determine whether it contained information on the topic of interest. We also scanned the cited references of retrieved articles to identify any additional relevant studies. Reference lists of review articles were also reviewed to check that the assembled list of relevant publications was complete.
the Universities of Newcastle, Australia, and Ottawa, Canada. It was primarily developed to assess the quality of non-randomized studies in the interpretation of meta-analytic results. The Newcastle–Ottawa scale develops a ‘star system’, whose goal is to provide an easy and convenient tool for quality assessment of nonrandomized studies to be used in a systematic review. Nonrandomized studies were judged on three broad perspectives as follows: the selection of study groups, comparability of groups and ascertainment of either the exposure or outcome of interest for prospective studies.
Data extraction and quality assessment
Statistical analysis
We independently evaluated the eligibility of all retrieved studies from the databases and extracted the relevant data from each included study using a unified data form. The items included in the data form were as follows: study name (together with the first author’s name and year of publication), journal name, location, study design, study population, inclusion criteria, exclusive criteria, range for follow-up and outcomes. The two lists from the authors were compared, and disagreements were resolved by consensus. Hazard ratio (HR) was recorded or calculated. If the study reported adjusted HRs, we prefer to extract-adjusted HRs into analysis. Otherwise, original HRs from raw data are included. The methodological quality of the included studies was assessed by means of the Newcastle–Ottawa scale for cohort studies.9 The Newcastle–Ottawa scale is an ongoing collaboration between
To compute a summary HR with its 95% confidence interval (CI), we used the study-specific most-adjusted HR and its 95% CI in all analyses. Publication bias was assessed via visual inspection of the funnel plots created by plotting the HR to standard error (SE) ([HR]) for included studies. We examined between-study heterogeneity using Cochran’s Q and I2 statistics. The I2 assess the percentage of variability in the effect estimates that is due to heterogeneity rather than chance. Fixed-effect model was presented if the P-value for heterogeneity was 50%. Otherwise, we would use the random effects model. We transformed the HR to a natural log scale and then calculated the SEs. The analysis was performed using STATA 12.0 software (StataCorp LP, College Station, TX, USA).
Fig. 1. Study selection diagram.
© 2014 Royal Australasian College of Surgeons
974
Zhou et al.
Results Literature search, study characteristics and quality assessment Figure 1 illustrates our search and selection process. The titles and abstracts of the primary 915 publications identified were reviewed and 834 were discarded after title and abstract review for one of the following reasons: they were not about cancer, they were not clinical studies or they were not human studies. Fifty more publications were also discarded after further evaluation for one of the following reasons: they were not about breast cancer, they did not evaluate the risk of diabetes mellitus, they did not evaluate prognostic outcomes or they did not apply to research question. Bibliographies were also searched for publications not identified in our database searches and
five more additional publications were found. The full text of total 36 articles was read through carefully. If the prognostic outcomes did not include mortality rate or no comparison was made between diabetic patients and non-diabetic patients, the publications were excluded. Finally, 20 publications were chosen for the meta-analysis,10–29 of which 16 studies10–17,20,22–25,27–29 had all-cause mortality data and 12 studies13,17–21,23–26,28,29 had breast cancer mortality data. The baseline characteristics of the studies included were summarized in Table 1. Published from 2001 to 2013, all 20 studies followed a total of 2 645 249 patients including more than 207 832 diabetic patients. Study-specific quality scores are summarized in Table 2. The range of quality scores was from 6 to 9. The median scores of included studies were 7.
Table 1 Characteristics of included studies Study
Year
No. of patients with DM
Total no.
Yancik
2001
NR
1800
Coughlin
2004
26 186
588 321
Du Tammemagi
2005 2005
73 127
588 906
Jee van de Poll-Franse
2005 2007
41 868 754
468 615 9725
Lipscombe
2008
1011
6107
Srokowski
2009
14 414
70 781
Zhou Seshasai
2010 2011
2103 40 116
44 655 820 900
Lam Irwin Schrauder
2011 2011 2011
23 560 58 276
367 361 604 4056
Liu
2011
1495
146 764
Yeh
2012
599
18 280
Redaniel
2012
52 657
82 867
Cleveland
2012
121
1447
Griffiths
2012
1784
2418
Chen
2012
341
4390
Nechuta
2013
289
4664
Age (years)
55–64 (35%) 65–74 (35%) >75 (31%) DM: mean, 61 NG: mean, 56 Mean 59 80 (9%) 49.6 DM: mean, 70.7 NG: mean, 58.9 DM: mean, 69.1 NG: mean, 68.0 66–70 (25%) 71–75 (27%) 76–80 (23%) 80+ (25%) 53.4 ± 9.5 DM: mean, 58 NG: mean, 55 48 58 DM: mean, 67.41 NG: mean, 56.85 DM: mean, 67 NG: mean, 60 DM: mean, 61.8 NG: mean, 51.5 70 (25.71%) DM: mean, 63.6 NG: mean, 57.4 DM: mean, 77.8 NG: mean, 77.7 DM: mean, 62.7 NG: mean, 53.0 20–75
Follow-up
Outcomes
30 months
All-cause mortality
16 years
All-cause mortality
3.68 years 10 (0.04–17.8) years
All-cause mortality All-cause mortality
10 years 3–10 years
Breast cancer mortality All-cause mortality
5 (0–10.9) years
All-cause mortality
2–12 years
All-cause mortality, breast cancer mortality
15.8 (9.1–23.2) years 13.6 years
Breast cancer mortality Breast cancer mortality
4 years 6 years 5 years
Breast cancer mortality All-cause mortality, breast cancer mortality All-cause mortality
7 years
Breast cancer mortality
17 years
All-cause mortality, breast cancer mortality
NR
All-cause mortality
96.4 (2.7–113.0) months
All-cause mortality, breast cancer mortality
NR
All-cause mortality, breast cancer mortality
67.2 months
All-cause mortality, breast cancer mortality
5.3 (0.64–8.9) years
All-cause mortality, breast cancer mortality
DM, diabetes mellitus; NG, normal glucose; NR, not reported.
© 2014 Royal Australasian College of Surgeons
Influence of diabetes mellitus
975
Table 2 Methodologic quality of cohort studies included in the meta-analysis Cohort studies
Year
Representativeness of the exposed cohort
Selection of the unexposed cohort
Yancik Coughlin Du Tammemagi Jee van de Poll-Franse Lipscombe Srokowski Zhou Seshasai Lam Irwin Schrauder Liu Yeh Redaniel Cleveland Griffiths Chen Nechuta
2001 2004 2005 2005 2005 2007
☆ ☆ ☆ ☆ ☆ ☆
☆ ☆ ☆ ☆ ☆ ☆
2008 2009 2010 2011 2011 2011 2011 2011 2012 2012 2012 2012 2012 2013
☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆
☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆
Ascertainment of exposure
☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆
Outcome of interest not present at start of study
Control for important factor or additional factor†
Outcome assessment
☆ ☆ ☆ ☆ ☆ ☆
☆ ☆☆ ☆☆ ☆☆ ☆☆ ☆☆
☆ ☆ ☆ ☆
☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆
☆☆ ☆☆ ☆☆ ☆☆ ☆☆ ☆☆ ☆☆ ☆☆ ☆☆ ☆☆ ☆☆ ☆☆ ☆☆ ☆☆
Follow-up long enough for outcomes to occur‡
☆ ☆ ☆ ☆ ☆ ☆
Adequacy of follow-up of cohorts§
Total quality scores
☆
☆ ☆
☆ ☆
☆ ☆
6 9 7 9 8 7
☆ ☆
☆ ☆
☆
☆
☆ ☆ ☆
☆
6 7 8 9 7 8 6 6 8 6 8 7 7 6
†A maximum of two stars could be awarded for this item. Studies that controlled for age received one star, whereas studies that controlled for other important confounders such as body mass index, smoking, family history of prostate cancer and so on received an additional star. ‡A cohort study with a follow-up time ≥8 years was assigned one star. §A cohort study with a follow-up rate >90% was assigned one star.
Table 3 Summary risk estimates of the association between diabetes mellitus and mortality of breast cancer patients Study
All-cause mortality Breast cancer mortality
16 12
HR (95% CI)
1.37 (1.34–1.41) 1.17 (1.11–1.22)
Egger’s test
0.021 0.509
Begg’s test
0.620 0.669
Heterogeneity test Q
P
I 2 (%)
35.33 59.51
0.002
