[Skip to Content]
Sign In
Individual Sign In
Create an Account
Institutional Sign In
OpenAthens Shibboleth
[Skip to Content Landing]
Download PDF
Table 1.  
Characteristics of Women With a Germline Mutation in a DNA Mismatch Repair Gene
Characteristics of Women With a Germline Mutation in a DNA Mismatch Repair Gene
Table 2.  
Hormonal and Reproductive Characteristics of Women With a Germline Mutation in a DNA Mismatch Repair Gene
Hormonal and Reproductive Characteristics of Women With a Germline Mutation in a DNA Mismatch Repair Gene
Table 3.  
Hazard Ratios for Associations Between the Risk of Endometrial Cancer and Endogenous Hormonal Factors for Women With a Germline Mutation in a DNA Mismatch Repair Gene
Hazard Ratios for Associations Between the Risk of Endometrial Cancer and Endogenous Hormonal Factors for Women With a Germline Mutation in a DNA Mismatch Repair Gene
Table 4.  
Hazard Ratios for Associations Between the Risk of Endometrial Cancer and Exogenous Hormonal Factors for Women With a Germline Mutation in a DNA Mismatch Repair Gene
Hazard Ratios for Associations Between the Risk of Endometrial Cancer and Exogenous Hormonal Factors for Women With a Germline Mutation in a DNA Mismatch Repair Gene
Supplement.

eTable 1. Assessment of interaction between main exposure variables and country of recruitment, ascertainment method, mutated mismatch repair gene, cigarette smoking status, and body mass index (BMI) at age 20 years

eTable 2. Hazard ratios for associations between the risk of endometrial cancer and hormonal factors for women with a germline mutation in a DNA mismatch repair gene – analysis restricted to women who were diagnosed with endometrial cancer or censored within 5 years before baseline interview

eTable 3. Hazard ratios for associations between the risk of endometrial cancer and endogenous hormonal factors for women with a germline mutation in a DNA mismatch repair gene by mutated gene

eTable 4. Hazard ratios for associations between the risk of endometrial cancer and exogenous hormonal factors for women with a germline mutation in a DNA mismatch repair gene by mutated gene

eTable 5. Hazard ratios for associations between reproductive factors and the risk of endometrial cancer for women with a germline mutation in a DNA mismatch repair gene by ascertainment method (population vs. clinic)

eTable 6. Hazard ratios for associations between the risk of endometrial cancer and exogenous hormonal factors for women with a germline mutation in a DNA mismatch repair gene by ascertainment method (population vs. clinic)

eTable 7. Hazard ratios for associations between the risk of endometrial cancer and hormonal factors for women with a germline mutation in a DNA mismatch repair gene – analysis that did not censor at age of first diagnosis of any other cancer

eTable 8. Hazard ratios for associations between the risk of endometrial cancer and hormonal factors for women with a germline mutation in a DNA mismatch repair gene – all models were adjusted for recent body mass index

1.
Amant  F, Moerman  P, Neven  P, Timmerman  D, Van Limbergen  E, Vergote  I.  Endometrial cancer. Lancet. 2005;366(9484):491-505.
PubMedArticle
2.
Sankaranarayanan  R, Ferlay  J.  Worldwide burden of gynaecological cancer: the size of the problem. Best Pract Res Clin Obstet Gynaecol. 2006;20(2):207-225.
PubMedArticle
3.
Meyer  LA, Broaddus  RR, Lu  KH.  Endometrial cancer and Lynch syndrome: clinical and pathologic considerations. Cancer Control. 2009;16(1):14-22.
PubMed
4.
Lynch  HT, Drescher  K, Knezetic  J, Lanspa  S.  Genetics, biomarkers, hereditary cancer syndrome diagnosis, heterogeneity and treatment: a review. Curr Treat Options Oncol. 2014;15(3):429-442.
PubMedArticle
5.
Hampel  H, de la Chapelle  A.  The search for unaffected individuals with Lynch syndrome: do the ends justify the means? Cancer Prev Res (Phila). 2011;4(1):1-5.
PubMedArticle
6.
Dowty  JG, Win  AK, Buchanan  DD,  et al.  Cancer risks for MLH1 and MSH2 mutation carriers. Hum Mutat. 2013;34(3):490-497.
PubMedArticle
7.
Baglietto  L, Lindor  NM, Dowty  JG,  et al; Dutch Lynch Syndrome Study Group.  Risks of Lynch syndrome cancers for MSH6 mutation carriers. J Natl Cancer Inst. 2010;102(3):193-201.
PubMedArticle
8.
Senter  L, Clendenning  M, Sotamaa  K,  et al.  The clinical phenotype of Lynch syndrome due to germ-line PMS2 mutations. Gastroenterology. 2008;135(2):419-428.
PubMedArticle
9.
Vasen  HFA, Watson  P, Mecklin  J-P, Lynch  HT.  New clinical criteria for hereditary nonpolyposis colorectal cancer (HNPCC, Lynch syndrome) proposed by the International Collaborative Group on HNPCC. Gastroenterology. 1999;116(6):1453-1456.
PubMedArticle
10.
Win  AK, Dowty  JG, Antill  YC,  et al.  Body mass index in early adulthood and endometrial cancer risk for mismatch repair gene mutation carriers. Obstet Gynecol. 2011;117(4):899-905.
PubMedArticle
11.
Zhang  Y, Liu  H, Yang  S, Zhang  J, Qian  L, Chen  X.  Overweight, obesity and endometrial cancer risk: results from a systematic review and meta-analysis. Int J Biol Markers. 2014;29(1):e21-e29.
PubMedArticle
12.
Ali  AT.  Reproductive factors and the risk of endometrial cancer. Int J Gynecol Cancer. 2014;24(3):384-393.
PubMedArticle
13.
Dossus  L, Allen  N, Kaaks  R,  et al.  Reproductive risk factors and endometrial cancer: the European Prospective Investigation into Cancer and Nutrition. Int J Cancer. 2010;127(2):442-451.
PubMed
14.
Lu  KH, Loose  DS, Yates  MS,  et al.  Prospective multicenter randomized intermediate biomarker study of oral contraceptive versus Depo-Provera for prevention of endometrial cancer in women with Lynch syndrome. Cancer Prev Res (Phila). 2013;6(8):774-781.
PubMedArticle
15.
Newcomb  PA, Baron  J, Cotterchio  M,  et al; Colon Cancer Family Registry.  Colon Cancer Family Registry: an international resource for studies of the genetic epidemiology of colon cancer. Cancer Epidemiol Biomarkers Prev. 2007;16(11):2331-2343.
PubMedArticle
16.
Rumilla  K, Schowalter  KV, Lindor  NM,  et al.  Frequency of deletions of EPCAM (TACSTD1) in MSH2-associated Lynch syndrome cases. J Mol Diagn. 2011;13(1):93-99.
PubMedArticle
17.
Southey  MC, Jenkins  MA, Mead  L,  et al.  Use of molecular tumor characteristics to prioritize mismatch repair gene testing in early-onset colorectal cancer. J Clin Oncol. 2005;23(27):6524-6532.
PubMedArticle
18.
Win  AK, Lindor  NM, Young  JP,  et al.  Risks of primary extracolonic cancers following colorectal cancer in Lynch syndrome. J Natl Cancer Inst. 2012;104(18):1363-1372.
PubMedArticle
19.
Antoniou  AC, Goldgar  DE, Andrieu  N,  et al.  A weighted cohort approach for analysing factors modifying disease risks in carriers of high-risk susceptibility genes. Genet Epidemiol. 2005;29(1):1-11.
PubMedArticle
20.
Curado  MP, Edwards  B, Shin  HR,  et al, eds. Cancer Incidence in Five Continents, Vol. IX. Lyon, France: International Agency for Research on Cancer; 2007. IARC Scientific Publications No. 160.
21.
Grambsch  PM, Therneau  TM.  Proportional hazards tests and diagnostics based on weighted residuals. Biometrika. 1994;81(3):515-526.Article
22.
Cleves  MA. An Introduction to Survival Analysis Using Stata.2nd ed. College Station, TX: Stata Press; 2008.
23.
Royston  P.  Multiple imputation of missing values: update. Stata J. 2005;5(2):188-201.
24.
Stata Multiple-Imputation Reference Manual Release 13 [computer program]. College Station, TX: StataCorp LP; 2013.
25.
Rogers  WH.  Regression standard errors in clustered samples. Stata Tech Bull. 1993;3(13):19-23.
26.
Williams  RL.  A note on robust variance estimation for cluster-correlated data. Biometrics. 2000;56(2):645-646.
PubMedArticle
27.
Fujita  M, Tase  T, Kakugawa  Y,  et al.  Smoking, earlier menarche and low parity as independent risk factors for gynecologic cancers in Japanese: a case-control study. Tohoku J Exp Med. 2008;216(4):297-307.
PubMedArticle
28.
Xu  W-H, Xiang  Y-B, Ruan  Z-X,  et al.  Menstrual and reproductive factors and endometrial cancer risk: results from a population-based case-control study in urban Shanghai. Int J Cancer. 2004;108(4):613-619.
PubMedArticle
29.
Schonfeld  SJ, Hartge  P, Pfeiffer  RM,  et al.  An aggregated analysis of hormonal factors and endometrial cancer risk by parity. Cancer. 2013;119(7):1393-1401.
PubMedArticle
30.
Haidopoulos  D, Simou  M, Akrivos  N,  et al.  Risk factors in women 40 years of age and younger with endometrial carcinoma. Acta Obstet Gynecol Scand. 2010;89(10):1326-1330.
PubMedArticle
31.
Gierisch  JM, Coeytaux  RR, Urrutia  RP,  et al.  Oral contraceptive use and risk of breast, cervical, colorectal, and endometrial cancers: a systematic review. Cancer Epidemiol Biomarkers Prev. 2013;22(11):1931-1943.
PubMedArticle
32.
Uharcek  P, Mlyncek  M, Ravinger  J, Matejka  M.  Prognostic factors in women 45 years of age or younger with endometrial cancer. Int J Gynecol Cancer. 2008;18(2):324-328.
PubMedArticle
33.
Zucchetto  A, Serraino  D, Polesel  J,  et al.  Hormone-related factors and gynecological conditions in relation to endometrial cancer risk. Eur J Cancer Prev. 2009;18(4):316-321.
PubMedArticle
34.
Pocobelli  G, Doherty  JA, Voigt  LF,  et al.  Pregnancy history and risk of endometrial cancer. Epidemiology. 2011;22(5):638-645.
PubMedArticle
35.
Setiawan  VW, Pike  MC, Karageorgi  S,  et al; Australian National Endometrial Cancer Study Group.  Age at last birth in relation to risk of endometrial cancer: pooled analysis in the epidemiology of endometrial cancer consortium. Am J Epidemiol. 2012;176(4):269-278.
PubMedArticle
36.
Blokhuis  MM, Pietersen  GE, Goldberg  PA,  et al.  Lynch syndrome: the influence of environmental factors on extracolonic cancer risk in hMLH1 c.C1528T mutation carriers and their mutation-negative sisters. Fam Cancer. 2010;9(3):357-363.
PubMedArticle
37.
Win  AK, Macinnis  RJ, Dowty  JG, Jenkins  MA.  Criteria and prediction models for mismatch repair gene mutations: a review. J Med Genet. 2013;50(12):785-793.
PubMedArticle
38.
MacDonald  ND, Salvesen  HB, Ryan  A, Iversen  OE, Akslen  LA, Jacobs  IJ.  Frequency and prognostic impact of microsatellite instability in a large population-based study of endometrial carcinomas. Cancer Res. 2000;60(6):1750-1752.
PubMed
39.
Amankwah  EK, Friedenreich  CM, Magliocco  AM,  et al.  Hormonal and reproductive risk factors for sporadic microsatellite stable and unstable endometrial tumors. Cancer Epidemiol Biomarkers Prev. 2013;22(7):1325-1331.
PubMedArticle
40.
Antoniou  AC, Spurdle  AB, Sinilnikova  OM,  et al; Kathleen Cuningham Consortium for Research into Familial Breast Cancer; OCGN; Swedish BRCA1 and BRCA2 Study Collaborators; DNA-HEBON Collaborators; EMBRACE; GEMO; CIMBA.  Common breast cancer-predisposition alleles are associated with breast cancer risk in BRCA1 and BRCA2 mutation carriers. Am J Hum Genet. 2008;82(4):937-948.
PubMedArticle
41.
Andrieu  N, Easton  DF, Chang-Claude  J,  et al.  Effect of chest X-rays on the risk of breast cancer among BRCA1/2 mutation carriers in the International BRCA1/2 Carrier Cohort Study: a report from the EMBRACE, GENEPSO, GEO-HEBON, and IBCCS Collaborators’ Group. J Clin Oncol. 2006;24(21):3361-3366.
PubMedArticle
42.
Crosbie  EJ, Zwahlen  M, Kitchener  HC, Egger  M, Renehan  AG.  Body mass index, hormone replacement therapy, and endometrial cancer risk: a meta-analysis. Cancer Epidemiol Biomarkers Prev. 2010;19(12):3119-3130.
PubMedArticle
43.
Grzankowski  KS, Shimizu  DM, Kimata  C, Black  M, Terada  KY.  Clinical and pathologic features of young endometrial cancer patients with loss of mismatch repair expression. Gynecol Oncol. 2012;126(3):408-412.
PubMedArticle
44.
Joehlin-Price  AS, Perrino  CM, Stephens  J,  et al.  Mismatch repair protein expression in 1049 endometrial carcinomas, associations with body mass index, and other clinicopathologic variables. Gynecol Oncol. 2014;133(1):43-47.
PubMedArticle
45.
Huang  M, Djordjevic  B, Yates  MS,  et al.  Molecular pathogenesis of endometrial cancers in patients with Lynch syndrome. Cancer. 2013;119(16):3027-3033.
PubMedArticle
46.
Lu  KH, Schorge  JO, Rodabaugh  KJ,  et al.  Prospective determination of prevalence of Lynch syndrome in young women with endometrial cancer. J Clin Oncol. 2007;25(33):5158-5164.
PubMedArticle
Original Investigation
July 7, 2015

Female Hormonal Factors and the Risk of Endometrial Cancer in Lynch Syndrome

Author Affiliations
  • 1Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia
  • 2Oncogenomics Group, Genetic Epidemiology Laboratory, Department of Pathology, The University of Melbourne
  • 3Departments of Haematology and Oncology, The Queen Elizabeth Hospital, Woodville, South Australia, Australia
  • 4SAHMRI Colorectal Node, Basil Hetzel Institute for Translational Research, Woodville, South Australia
  • 5School of Medicine, University of Adelaide, South Australia
  • 6Department of Medicine, The University of Melbourne
  • 7Genetic Medicine, The Royal Melbourne Hospital, Parkville, Victoria, Australia
  • 8New Zealand Familial Gastrointestinal Cancer Service, Auckland, New Zealand
  • 9Department of Medicine, University of Colorado School of Medicine, Denver
  • 10Division of Oncology, Department of Medicine, Stanford Cancer Institute, Stanford University, Stanford, California
  • 11Department of Preventive Medicine, Keck School of Medicine and Norris Comprehensive Cancer Center, University of Southern California, Los Angeles
  • 12Lunenfeld Tanenbaum Research Institute, Mount Sinai Hospital, University of Toronto, Toronto, Ontario, Canada
  • 13Molecular Genetics Laboratory, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota
  • 14Department of Health Science Research, Mayo Clinic Arizona, Scottsdale
  • 15University of Hawaii Cancer Center, Honolulu
  • 16Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington
  • 17School of Public Health, University of Washington, Seattle
  • 18Centre for Public Health Research, Massey University, Wellington, New Zealand
  • 19Department of Medicine, University of North Carolina, Chapel Hill
  • 20Department of Epidemiology and Institute of Health and Environment, School of Public Health, Seoul National University, Seoul, Korea
JAMA. 2015;314(1):61-71. doi:10.1001/jama.2015.6789
Abstract

Importance  Apart from hysterectomy, there is no consensus recommendation for reducing endometrial cancer risk for women with a mismatch repair gene mutation (Lynch syndrome).

Objective  To investigate the association between hormonal factors and endometrial cancer risk in Lynch syndrome.

Design, Setting, and Participants  A retrospective cohort study included 1128 women with a mismatch repair gene mutation identified from the Colon Cancer Family Registry. Data were analyzed with a weighted cohort approach. Participants were recruited between 1997 and 2012 from centers across the United States, Australia, Canada, and New Zealand.

Exposures  Age at menarche, first and last live birth, and menopause; number of live births; hormonal contraceptive use; and postmenopausal hormone use.

Main Outcomes and Measures  Self-reported diagnosis of endometrial cancer.

Results  Endometrial cancer was diagnosed in 133 women (incidence rate per 100 person-years, 0.29; 95% CI, 0.24 to 0.34). Endometrial cancer was diagnosed in 11% (n = 70) of women with age at menarche greater than or equal to 13 years compared with 12.6% (n = 57) of women with age at menarche less than 13 years (incidence rate per 100 person-years, 0.27 vs 0.31; rate difference, −0.04 [95% CI, −0.15 to 0.05]; hazard ratio per year, 0.85 [95% CI, 0.73 to 0.99]; P = .04). Endometrial cancer was diagnosed in 10.8% (n = 88) of parous women compared with 14.4% (n = 40) of nulliparous women (incidence rate per 100 person-years, 0.25 vs 0.43; rate difference, −0.18 [95% CI, −0.32 to −0.04]; hazard ratio, 0.21 [95% CI, 0.10 to 0.42]; P < .001). Endometrial cancer was diagnosed in 8.7% (n = 70) of women who used hormonal contraceptives greater than or equal to 1 year compared with 19.2% (n = 57) of women who used contraceptives less than 1 year (incidence rate per 100 person-years, 0.22 vs 0.45; rate difference, −0.23 [95% CI, −0.36 to −0.11]; hazard ratio, 0.39 [95% CI, 0.23 to 0.64]; P < .001). There was no statistically significant association between endometrial cancer and age at first and last live birth, age at menopause, and postmenopausal hormone use.

Conclusions and Relevance  For women with a mismatch repair gene mutation, some endogenous and exogenous hormonal factors were associated with a lower risk of endometrial cancer. These directions and strengths of associations were similar to those for the general population. If replicated, these findings suggest that women with a mismatch repair gene mutation may be counseled like the general population in regard to hormonal influences on endometrial cancer risk.

Introduction

Endometrial cancer is the most common type of gynecologic cancer in developed countries.1,2 Between 2% and 5% of all endometrial cancer cases are associated with a hereditary susceptibility to cancer, mainly Lynch syndrome,3 which is an autosomal dominant disorder caused by a germline mutation in one of the DNA mismatch repair (MMR) genes MLH1 (RefSeq NM_000249), MSH2 (RefSeq NM_000251), MSH6 (RefSeq NM_000179), PMS2 (RefSeq NM_000535), and EPCAM (RefSeq NM_000535).4 Although estimates vary, the incidence of Lynch syndrome may be as high as 1 in 370 in the general population in the United States.5 Depending on the mutated gene, cumulative risk of developing endometrial cancer by age 70 years for women is thought to be between 15% and 30%.68 Apart from hysterectomy, there is no consensus recommendation for reducing endometrial cancer risk for women with an MMR gene mutation.9,10

Studies in the general population have shown that factors that increase the bioavailability of estrogen unopposed by progesterone, including obesity,11 early age at menarche, late age at menopause, nulliparity, and use of estrogen-only menopausal hormone therapy, increase endometrial cancer risk.12,13 On the other hand, hormonal contraceptive use, higher number of pregnancies, and later age at first and last live birth have been shown to reduce endometrial cancer risk.12,13

For Lynch syndrome, the association between female hormonal factors and endometrial cancer risk is not clear. Results from a multicenter randomized trial that studied the influence of oral contraceptive and medroxyprogesterone acetate on endometrial proliferation in 51 women with Lynch syndrome suggested that, similar to that in the general population, short-term exposure to exogenous progesterone reduced endometrial epithelial proliferation in this group of women.14

In the present study, we estimated the associations between endometrial cancer risk and hormonal factors for women with an MMR gene mutation.

Methods
Study Sample

This was a retrospective cohort study that included women with a heterozygous germline pathogenic mutation in an MMR gene who had been recruited by the Colon Cancer Family Registry. Study design and recruitment strategy have been published in detail and are available at http://coloncfr.org.15 Probands were those who had either recently received a diagnosis of colorectal cancer that was reported to state or regional population cancer registries in the United States (Washington, Minnesota, California, Arizona, Colorado, New Hampshire, North Carolina, and Hawaii), Australia (Victoria), and Canada (Ontario) or were from multiple-case families referred to family-cancer clinics in the United States (Mayo Clinic, Rochester, Minnesota; and Cleveland Clinic, Cleveland, Ohio), Canada (Ontario), Australia (Melbourne, Adelaide, Perth, Brisbane, and Sydney), and New Zealand (Auckland). Individuals were recruited and interviewed between 1997 and 2012 and were asked for permission to contact their relatives and seek their enrollment in the Colon Cancer Family Registry. For population-based families, first-degree relatives of probands were recruited at all centers, and at some centers, recruitment was extended to more distant relatives. For clinic-based families, recruitment was attempted up to second-degree relatives of affected individuals (details are provided by Newcomb et al15). Participants were followed up approximately every 5 years after baseline to update this information. For this study, 2011 was the last date of outcome assessment and censoring. Informed consent was obtained from all study participants, and the study protocol was approved at each involved center by the institutional research ethics review board.

Data Collection

At recruitment (baseline), information on demographics, personal characteristics, personal and family history of cancer, and history of cancer screening and any surgery including gynecologic surgery was obtained with standardized questionnaires via personal interviews, telephone interviews, or mailed questionnaires from all participants. The questionnaires used at each Colon Cancer Family Registry center are available at http://coloncfr.org/questionnaires. When possible, reported cancer diagnoses and age at diagnosis were confirmed with pathology review and reports, medical records, cancer registry reports, or death certificates. We attempted to obtain blood samples from all participants and tumor tissue samples from all participants affected with colorectal cancer.

MMR Gene Mutation Testing

Testing for germline mutations in MLH1, MSH2, MSH6, and PMS2 was performed for all population-based probands who had a colorectal tumor displaying evidence of impaired MMR function, as evidenced by tumor microsatellite instability or lack of MMR-protein expression in immunohistochemical analysis. Testing was undertaken for the youngest-onset colorectal cancer participant from each clinic-based family regardless of microsatellite instability or MMR-protein expression status. Mutation testing for the MLH1, MSH2, and MSH6 genes was performed by Sanger sequencing or denaturing high-performance liquid chromatography, followed by confirmatory DNA sequencing. Large duplication and deletion mutations were detected by multiplex ligation-dependent probe amplification according to the manufacturer’s instructions (MRC Holland).1517PMS2 mutation testing involved a modified protocol from Senter et al8 in which exons 1 through 5, 9, and 11 through 15 were amplified in 3 long-range polymerase chain reactions, followed by nested exon-specific polymerase chain reaction and sequencing, with the remaining exons (6, 7, 8, and 10) being amplified and sequenced directly from genomic DNA. Large-scale deletions in PMS2 were detected with the P008-A1 multiplex ligation-dependent probe amplification kit (MRC Holland). Relatives of probands with a pathogenic MMR germline mutation18 who provided a blood sample underwent testing for the specific mutation identified in the proband.

Statistical Analysis

Cox proportional regression models with age as the time scale were used to estimate any association between female hormonal factors (see Box for definitions) and endometrial cancer risk. Time at risk started at birth and ended at age of endometrial cancer diagnosis, any other cancer diagnosis, hysterectomy, or interview, whichever occurred first. We censored at age of diagnosis of any primary cancer because resultant treatment and surveillance might have altered endometrial cancer risk. In addition, carriers might have changed their behavior after the diagnosis of cancer.

Box Section Ref ID
Box.

Definitions of Outcome and Exposures

  • All the definitions were decided before analysis of the data.

  • Primary Outcome: Self-reported diagnosis of endometrial cancer

  • Primary Exposures: Self-reported endogenous and exogenous hormonal factors

  • Age at menarche was defined as age at first menstrual cycle.

  • Number of live births was defined as the number of pregnancies that resulted in a live birth. Given that the questionnaires did not elicit age at each birth, we defined number of live births according to self-reported number of live births, age at first and last live birth, and censored age. Women with age at first live birth younger than censored age were categorized as parous, and those with age at first live birth older than censored age were categorized as nulliparous.

  • Ever use of hormonal contraceptive was defined as use of oral contraceptives or other hormonal contraceptives (implants or injections) for at least 1 year. In accordance with the reported age at first use and number of years of hormonal contraception use, and assuming that the use had been continuous, age at last use of hormonal contraception was calculated. When this age was older than censored age, years of hormonal contraception use was calculated according to censored age and age at first use.

  • Age at menopause was defined as age when menstrual cycles had stopped for at least 12 months. Natural menopause was defined as self-reported cessation of menstrual cycles for at least 12 months. Induced menopause was defined as cessation of menstrual cycles for at least 12 months because of gynecologic surgery, radiation or chemotherapy, or other reasons.

  • Women with unknown menopausal status were assumed to have had natural menopause if they were aged 60 years or older at censoring. For this group of women, age at menopause was considered to be 56 years, which was the oldest age at natural menopause reported in this cohort.

  • Ever use of postmenopausal hormones was use of a pill or patch for at least 1 year. Estrogen-only use was defined as having used estrogen-only pills or patches for at least 1 year. Estrogen and progesterone combination was defined as having used progesterone along with estrogen for at least 1 year. In accordance with the reported age at first use and number of years of postmenopausal hormone use, and assuming that the use had been continuous, age at last use of postmenopausal hormone was calculated. When this age was older than the censored age, years of postmenopausal hormone use were calculated according to censored age and age at first use.

Because a proportion of women in this study was ascertained from multiple-case cancer families and cases were tested preferentially for MMR gene mutations, selection of women was not random with respect to disease status. To take this nonrandom ascertainment of cases into account, we applied probability weights to women according to the approach described by Antoniou et al.19 Age-specific incidences of endometrial cancer for women were calculated by multiplying the country- and age-specific population incidences by the hazard ratio of endometrial cancer for women with a specific MMR gene mutation. Average age-specific population incidences in 1998-2002 for each country (Australia, Canada, and the United States) were obtained from Cancer Incidence in Five Continents.20 These age-specific incidences of endometrial cancer for women with MMR gene mutations were used to calculate statistical weights for women with and without endometrial cancer in each age stratum.

The proportional hazards assumption was tested with the Schoenfeld and scaled Schoenfeld residuals.21 Bivariable and multivariable models were fit separately for each hormonal factor. The variables that we considered potential confounders are listed in Table 1. The variables that did not meet the proportional hazards assumption were included as time-dependent covariates in the model. Tests for interactions were assessed by a change in the log-likelihood ratio after the addition of a cross-product term between the exposure and potential effect modifiers identified a priori. The overall model fit was assessed with Cox-Snell residuals as the time variable, plotting them against the Nelson-Aalen cumulative hazard function.22

For multivariable models, missing data were handled with both complete case analysis and multiple imputation. Numbers of missing values for all the variables are reported in Table 1 and Table 2. Assuming that missing was at random, missing data were imputed with chained equations.23,24 Variables included in the imputation model were outcome status, age at endometrial cancer diagnosis or censored age, year of birth, country, mutated gene, ascertainment method (clinic vs population), and whether the carrier was a proband. Fifty imputed data sets were created.

When age variables (ie, age at menarche, age at first and last live birth, and age at menopause) were the primary exposures, we analyzed them as categorical variables, as well as continuous variables, in 2 different models. We used the median values as the cutoff points to categorize these variables.

We conducted the following additional analyses: analyses restricted to women who received a diagnosis of endometrial cancer or whose data were censored within 5 years before interview to reduce survival bias; analyses restricted to women with verified endometrial cancer diagnosis and unaffected women; analyses for women ascertained through clinic-based and population-based resources, and for the 4 mutated MMR genes; and analyses in which we did not censor data for women at age of first diagnosis of any other cancer.

To account for potential correlation of risk between family members, the Huber-White robust variance correction was used by clustering on family membership.25,26 All statistical tests were 2-sided and P < .05 was considered statistically significant. All statistical analyses were performed with Stata version 13.0.

Results

We identified 1133 women with an MMR gene mutation from the Colon Cancer Family Registry. Of these, 5 (0.4%) who were younger than 18 years were excluded. The final sample included 1128 women from 548 independent families, contributing a total of 45 831 person-years. Of these women, 424 carried a mutation in MLH1, 532 in MSH2, 117 in MSH6, and 55 in PMS2.

Time at risk ended at age at endometrial cancer diagnosis for 133 women, any other cancer diagnosis for 417, hysterectomy for 229, and interview for 349. In this cohort, endometrial cancer incidence rate was 0.29 per 100 person-years (95% CI, 0.24-0.34), with a mean (SD) age at diagnosis of 45.9 years (8.2). We were able to confirm endometrial cancer diagnosis for 101 women (76%) by pathology review or report, cancer registries, or hospital record. Characteristics of women included in this study are summarized in Table 1 and Table 2.

The results of Cox regression models and adjusted variables in each model are summarized in Table 3 and Table 4. There was a statistically significant association between later age at menarche and a lower risk of endometrial cancer (endometrial cancer incidence rate per 100 person-years for women with age at menarche ≥13 vs <13 years: 0.27 vs 0.31; rate difference, −0.04 [95% CI, −0.15 to 0.05]; hazard ratio per year, 0.85 [95% CI, 0.73 to 0.99]; P = .04). There was also an inverse association between endometrial cancer risk and parity (incidence rate per 100 person-years for parous vs nulliparous women: 0.25 vs 0.43; rate difference, −0.18 [95% CI, −0.32 to −0.04]; hazard ratio, 0.21 [95% CI, 0.10 to 0.42]; P < .001). We did not observe a statistically significant association between endometrial cancer risk and age at first live birth (P = .46), age at last live birth (P = .62), or age at menopause (P = .96) (Table 3).

Ever use of hormonal contraceptives was associated with a lower endometrial cancer risk compared with never use (incidence rate per 100 person-years for ≥1 year vs <1 year use: 0.22 vs 0.45; rate difference, −0.23 [95% CI, −0.36 to −0.11]; hazard ratio, 0.39 [95% CI, 0.23 to 0.64]; P < .001). There was no statistically significant association between postmenopausal hormone use and endometrial cancer risk (P = .57), even after stratifying the type of postmenopausal hormone (estrogen only or estrogen and progestin combination) (Table 4). Because of the small number of women (1%) who reported use of antiestrogen drugs (including tamoxifen and raloxifene), we were unable to investigate associations between these drugs and endometrial cancer risk.

There was no statistically significant evidence that cigarette smoking status, body mass index (BMI) at age 20 years, country of residence, specific MMR gene mutation, and ascertainment method modified any of the observed associations (eTable 1 in the Supplement).

In an analysis restricted to women who received a diagnosis of endometrial cancer or whose data were censored within 5 years before interview, we found results similar to those of the main analysis (eTable 2 in the Supplement). In sensitivity analyses restricted to women with verified endometrial cancer diagnosis and unaffected women, results were similar to those of the main analysis. Although the statistical power was poor, the patterns of associations remained the same in analyses stratified by ascertainment (clinic and population based) and by mutated gene (MLH1, MLH2, MSH6, and PMS2) (eTables 3-6 in the Supplement). We also observed similar results in analyses that did not censor data for women at their age of first diagnosis of any other cancer (eTable 7 in the Supplement). When we additionally adjusted for recent BMI in the multiple imputation analyses, the results were similar to those of the main analyses (eTable 8 in the Supplement).

There was no evidence that main exposure variables violated the proportional hazards assumption in any of the final models. The directions and strengths of associations were similar in both unweighted and weighted cohort analyses, although the standard errors of the estimates were increased in weighted analyses.

Discussion

In this study, an inverse association was observed between the risk of endometrial cancer for women with an MMR gene mutation and later age of menarche, increased parity, and use of hormonal contraceptives. The directions of the observed associations are similar to those that have been reported for the general population, suggesting a possible protective effect of these factors.12,13,2731 Unlike observations for women from the general population,12,13,32,33 there was no statistically significant association between age at menopause and endometrial cancer risk in Lynch syndrome. Approximately 80% of women in our cohort were premenopausal and age at menopause was unknown for approximately 22% of postmenopausal women. Similarly, we did not observe a statistically significant association between endometrial cancer risk and age at first and last live birth in Lynch syndrome, which is in accordance with some13,34 but not all studies34,35 conducted in the general population.36 The lack of an observed association between endometrial cancer risk and postmenopausal hormone use in this study could be attributed to lack of statistical power (only 2.8% of women reported use of estrogen only and 4.3% reported use of combined estrogen and progesterone for at least 1 year). Additional unmeasured confounding or information bias could also account for this finding.

Given that Lynch syndrome–associated cancers typically exhibit high levels of microsatellite instability or loss of MMR protein expression as measured by immunohistochemical staining, these tests have been widely used as screening methods for likely MMR germline mutation carriers. However, neither of these tests is diagnostic and germline testing is required to confirm mutation carrier status.37 For example, microsatellite instability is observed in approximately 30% of sporadic endometrial cancers.38 Amankwah et al39 investigated the association between hormonal factors and the risk of microsatellite-stable (n = 103) and microsatellite-unstable (n = 258) endometrial cancer. They reported a reduced risk of microsatellite-unstable endometrial cancer for parous women compared with nulliparous women (odds ratio, 0.53 [95% CI, 0.28-1.02]) and for women who received oral contraceptives for at least 5 years compared with those who received them for fewer than 6 months (odds ratio, 0.43 [95% CI, 0.23-0.77]), results similar to ours. There was an increasing risk reduction of endometrial cancer associated with a longer duration of oral contraceptives use and a stronger inverse association for women with a microsatellite-unstable tumor compared with those with a microsatellite-stable tumor.

An inverse association between endometrial proliferation and hormonal contraceptives in Lynch syndrome was also reported in a multicenter randomized trial.14 In that study, 51 women with a known MMR gene mutation or a history of Lynch syndrome–associated cancer who met Amsterdam criteria were randomly assigned to receive either oral contraceptive pills or medroxyprogesterone acetate for 3 months and assessed for endometrial proliferation before and after treatment. A significant decrease in endometrial epithelial proliferation was observed posttreatment in both groups, suggesting that hormonal contraceptives may be useful chemopreventive agents in these women at high risk. Our results provide further evidence supporting the hypothesis that long-term exposure to hormonal contraceptives may significantly reduce the risk of endometrial cancer in Lynch syndrome.

To the best of our knowledge, this is the largest study to date investigating the association between endometrial cancer risk and hormonal factors in Lynch syndrome. To overcome bias in retrospective studies in which subjects are selected on the basis of disease, we used a weighted cohort approach,19 which has been successfully used in studies of modifiers of cancer risk associated with rare genetic mutations.10,40,41 Data for this study came from the Colon Cancer Family Registry, which used standardized and uniform materials for collection of epidemiology, family, and cancer data, as well as genetic testing.

Our study had several limitations. There might be errors in measurements of exposure variables and other adjusted variables because they came from self-reported questionnaires. For individuals who received a diagnosis of endometrial cancer or whose data were censored at an age younger than their age at interview, years of hormonal contraception and postmenopausal hormone use were calculated according to self-reported age at first use and number of years of hormone use, assuming that use had been continuous. This method may have overestimated the years of hormone use for some carriers. However, this potential misclassification would more probably bias the results toward the null and would not account for the observed inverse association between endometrial cancer risk and years of hormonal contraceptive use. Recall of all exposure may have been affected by disease status in our cohort because women received a diagnosis of endometrial cancer before interview. To determine whether survival bias influenced the observed associations, we conducted a sensitivity analysis restricted to women who received a diagnosis of endometrial cancer or whose data were censored within 5 years before interview; we observed findings similar to those of the main analysis. Another potential limitation of our study is the lack of a valid measure of recent BMI for 52% of all women. BMI is a strong and consistent risk factor for endometrial cancer and has been reported to be a confounder for the association between endometrial cancer risk and hormonal factors for the general population.11,42 However, there is some evidence that recent BMI is not associated with endometrial cancer in Lynch syndrome.4346 In our complete case analysis, BMI at age 20 years was available and did not confound or modify the association between endometrial cancer risk and any hormonal factors. Furthermore, imputed recent BMI did not confound any of those associations.

Conclusions

For women with an MMR gene mutation, some endogenous and exogenous hormonal factors were associated with a lower risk of endometrial cancer. These directions and strengths of associations were similar to those for the general population. If replicated, these findings suggest that women with an MMR gene mutation may be counseled like the general population in regard to hormonal influences on endometrial cancer risk.

Back to top
Article Information

Corresponding Author: Aung Ko Win, MBBS, PhD, MPH, Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, Level 3, 207 Bouverie St, University of Melbourne, VIC 3010, Australia (awin@unimelb.edu.au).

Author Contributions: Drs Dashti and Win had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: Chau, Hopper, Jenkins, Win.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Dashti, Chau, Ouakrim, Winship, Jenkins, Win.

Critical revision of the manuscript for important intellectual content: Chau, Buchanan, Clendenning, Young, Winship, Arnold, Ahnen, Haile, Casey, Gallinger, Thibodeau, Lindor, Le Marchand, Newcomb, Potter, Baron, Hopper.

Statistical analysis: Dashti, Chau, Ouakrim, Jenkins, Win.

Obtained funding: Ahnen, Gallinger, Le Marchand, Newcomb, Potter, Hopper, Jenkins, Win.

Administrative, technical, or material support: Buchanan, Clendenning, Young, Thibodeau, Le Marchand, Newcomb, Hopper, Jenkins.

Study supervision: Winship, Ahnen, Hopper, Jenkins, Win.

Conflict of Interest Disclosures: All authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Dr Ahnen reports serving on the scientific advisory board for EXACT Sciences Inc and Cancer Prevention Pharmaceuticals. No other disclosures were reported.

Funding/Support: This work was supported by grant UM1 CA167551 from the National Cancer Institute, National Institutes of Health, and through cooperative agreements with members of the Colon Cancer Family Registry and principal investigators. Collaborating centers include the Australasian Colorectal Cancer Family Registry (U01/U24 CA097735), Mayo Clinic Cooperative Family Registry for Colon Cancer Studies (U01/U24 CA074800), Ontario Familial Colorectal Cancer Registry (U01/U24 CA074783), Seattle Colorectal Cancer Family Registry (U01/U24 CA074794), Stanford Consortium Colorectal Cancer Family Registry (U01/U24 CA074799), and University of Hawaii Colorectal Cancer Family Registry (U01/U24 CA074806). This work was also supported by Centre for Research Excellence grant APP1042021 and program grant APP1074383 from the National Health and Medical Research Council (NHMRC), Australia. Dr Win is an NHMRC Early Career Fellow. Dr Jenkins is an NHMRC Senior Research Fellow. Dr Hopper is an NHMRC Senior Principal Research Fellow. Dr Buchanan is a University of Melbourne Research at Melbourne Accelerator Program Senior Research Fellow.

Role of the Funder/Sponsor: The sponsors had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Disclaimer: The content of this article does not necessarily reflect the views or policies of the National Cancer Institute or any of the collaborating centers in the CFRs, nor does mention of trade names, commercial products, or organizations imply endorsement by the US government or the CFR.

References
1.
Amant  F, Moerman  P, Neven  P, Timmerman  D, Van Limbergen  E, Vergote  I.  Endometrial cancer. Lancet. 2005;366(9484):491-505.
PubMedArticle
2.
Sankaranarayanan  R, Ferlay  J.  Worldwide burden of gynaecological cancer: the size of the problem. Best Pract Res Clin Obstet Gynaecol. 2006;20(2):207-225.
PubMedArticle
3.
Meyer  LA, Broaddus  RR, Lu  KH.  Endometrial cancer and Lynch syndrome: clinical and pathologic considerations. Cancer Control. 2009;16(1):14-22.
PubMed
4.
Lynch  HT, Drescher  K, Knezetic  J, Lanspa  S.  Genetics, biomarkers, hereditary cancer syndrome diagnosis, heterogeneity and treatment: a review. Curr Treat Options Oncol. 2014;15(3):429-442.
PubMedArticle
5.
Hampel  H, de la Chapelle  A.  The search for unaffected individuals with Lynch syndrome: do the ends justify the means? Cancer Prev Res (Phila). 2011;4(1):1-5.
PubMedArticle
6.
Dowty  JG, Win  AK, Buchanan  DD,  et al.  Cancer risks for MLH1 and MSH2 mutation carriers. Hum Mutat. 2013;34(3):490-497.
PubMedArticle
7.
Baglietto  L, Lindor  NM, Dowty  JG,  et al; Dutch Lynch Syndrome Study Group.  Risks of Lynch syndrome cancers for MSH6 mutation carriers. J Natl Cancer Inst. 2010;102(3):193-201.
PubMedArticle
8.
Senter  L, Clendenning  M, Sotamaa  K,  et al.  The clinical phenotype of Lynch syndrome due to germ-line PMS2 mutations. Gastroenterology. 2008;135(2):419-428.
PubMedArticle
9.
Vasen  HFA, Watson  P, Mecklin  J-P, Lynch  HT.  New clinical criteria for hereditary nonpolyposis colorectal cancer (HNPCC, Lynch syndrome) proposed by the International Collaborative Group on HNPCC. Gastroenterology. 1999;116(6):1453-1456.
PubMedArticle
10.
Win  AK, Dowty  JG, Antill  YC,  et al.  Body mass index in early adulthood and endometrial cancer risk for mismatch repair gene mutation carriers. Obstet Gynecol. 2011;117(4):899-905.
PubMedArticle
11.
Zhang  Y, Liu  H, Yang  S, Zhang  J, Qian  L, Chen  X.  Overweight, obesity and endometrial cancer risk: results from a systematic review and meta-analysis. Int J Biol Markers. 2014;29(1):e21-e29.
PubMedArticle
12.
Ali  AT.  Reproductive factors and the risk of endometrial cancer. Int J Gynecol Cancer. 2014;24(3):384-393.
PubMedArticle
13.
Dossus  L, Allen  N, Kaaks  R,  et al.  Reproductive risk factors and endometrial cancer: the European Prospective Investigation into Cancer and Nutrition. Int J Cancer. 2010;127(2):442-451.
PubMed
14.
Lu  KH, Loose  DS, Yates  MS,  et al.  Prospective multicenter randomized intermediate biomarker study of oral contraceptive versus Depo-Provera for prevention of endometrial cancer in women with Lynch syndrome. Cancer Prev Res (Phila). 2013;6(8):774-781.
PubMedArticle
15.
Newcomb  PA, Baron  J, Cotterchio  M,  et al; Colon Cancer Family Registry.  Colon Cancer Family Registry: an international resource for studies of the genetic epidemiology of colon cancer. Cancer Epidemiol Biomarkers Prev. 2007;16(11):2331-2343.
PubMedArticle
16.
Rumilla  K, Schowalter  KV, Lindor  NM,  et al.  Frequency of deletions of EPCAM (TACSTD1) in MSH2-associated Lynch syndrome cases. J Mol Diagn. 2011;13(1):93-99.
PubMedArticle
17.
Southey  MC, Jenkins  MA, Mead  L,  et al.  Use of molecular tumor characteristics to prioritize mismatch repair gene testing in early-onset colorectal cancer. J Clin Oncol. 2005;23(27):6524-6532.
PubMedArticle
18.
Win  AK, Lindor  NM, Young  JP,  et al.  Risks of primary extracolonic cancers following colorectal cancer in Lynch syndrome. J Natl Cancer Inst. 2012;104(18):1363-1372.
PubMedArticle
19.
Antoniou  AC, Goldgar  DE, Andrieu  N,  et al.  A weighted cohort approach for analysing factors modifying disease risks in carriers of high-risk susceptibility genes. Genet Epidemiol. 2005;29(1):1-11.
PubMedArticle
20.
Curado  MP, Edwards  B, Shin  HR,  et al, eds. Cancer Incidence in Five Continents, Vol. IX. Lyon, France: International Agency for Research on Cancer; 2007. IARC Scientific Publications No. 160.
21.
Grambsch  PM, Therneau  TM.  Proportional hazards tests and diagnostics based on weighted residuals. Biometrika. 1994;81(3):515-526.Article
22.
Cleves  MA. An Introduction to Survival Analysis Using Stata.2nd ed. College Station, TX: Stata Press; 2008.
23.
Royston  P.  Multiple imputation of missing values: update. Stata J. 2005;5(2):188-201.
24.
Stata Multiple-Imputation Reference Manual Release 13 [computer program]. College Station, TX: StataCorp LP; 2013.
25.
Rogers  WH.  Regression standard errors in clustered samples. Stata Tech Bull. 1993;3(13):19-23.
26.
Williams  RL.  A note on robust variance estimation for cluster-correlated data. Biometrics. 2000;56(2):645-646.
PubMedArticle
27.
Fujita  M, Tase  T, Kakugawa  Y,  et al.  Smoking, earlier menarche and low parity as independent risk factors for gynecologic cancers in Japanese: a case-control study. Tohoku J Exp Med. 2008;216(4):297-307.
PubMedArticle
28.
Xu  W-H, Xiang  Y-B, Ruan  Z-X,  et al.  Menstrual and reproductive factors and endometrial cancer risk: results from a population-based case-control study in urban Shanghai. Int J Cancer. 2004;108(4):613-619.
PubMedArticle
29.
Schonfeld  SJ, Hartge  P, Pfeiffer  RM,  et al.  An aggregated analysis of hormonal factors and endometrial cancer risk by parity. Cancer. 2013;119(7):1393-1401.
PubMedArticle
30.
Haidopoulos  D, Simou  M, Akrivos  N,  et al.  Risk factors in women 40 years of age and younger with endometrial carcinoma. Acta Obstet Gynecol Scand. 2010;89(10):1326-1330.
PubMedArticle
31.
Gierisch  JM, Coeytaux  RR, Urrutia  RP,  et al.  Oral contraceptive use and risk of breast, cervical, colorectal, and endometrial cancers: a systematic review. Cancer Epidemiol Biomarkers Prev. 2013;22(11):1931-1943.
PubMedArticle
32.
Uharcek  P, Mlyncek  M, Ravinger  J, Matejka  M.  Prognostic factors in women 45 years of age or younger with endometrial cancer. Int J Gynecol Cancer. 2008;18(2):324-328.
PubMedArticle
33.
Zucchetto  A, Serraino  D, Polesel  J,  et al.  Hormone-related factors and gynecological conditions in relation to endometrial cancer risk. Eur J Cancer Prev. 2009;18(4):316-321.
PubMedArticle
34.
Pocobelli  G, Doherty  JA, Voigt  LF,  et al.  Pregnancy history and risk of endometrial cancer. Epidemiology. 2011;22(5):638-645.
PubMedArticle
35.
Setiawan  VW, Pike  MC, Karageorgi  S,  et al; Australian National Endometrial Cancer Study Group.  Age at last birth in relation to risk of endometrial cancer: pooled analysis in the epidemiology of endometrial cancer consortium. Am J Epidemiol. 2012;176(4):269-278.
PubMedArticle
36.
Blokhuis  MM, Pietersen  GE, Goldberg  PA,  et al.  Lynch syndrome: the influence of environmental factors on extracolonic cancer risk in hMLH1 c.C1528T mutation carriers and their mutation-negative sisters. Fam Cancer. 2010;9(3):357-363.
PubMedArticle
37.
Win  AK, Macinnis  RJ, Dowty  JG, Jenkins  MA.  Criteria and prediction models for mismatch repair gene mutations: a review. J Med Genet. 2013;50(12):785-793.
PubMedArticle
38.
MacDonald  ND, Salvesen  HB, Ryan  A, Iversen  OE, Akslen  LA, Jacobs  IJ.  Frequency and prognostic impact of microsatellite instability in a large population-based study of endometrial carcinomas. Cancer Res. 2000;60(6):1750-1752.
PubMed
39.
Amankwah  EK, Friedenreich  CM, Magliocco  AM,  et al.  Hormonal and reproductive risk factors for sporadic microsatellite stable and unstable endometrial tumors. Cancer Epidemiol Biomarkers Prev. 2013;22(7):1325-1331.
PubMedArticle
40.
Antoniou  AC, Spurdle  AB, Sinilnikova  OM,  et al; Kathleen Cuningham Consortium for Research into Familial Breast Cancer; OCGN; Swedish BRCA1 and BRCA2 Study Collaborators; DNA-HEBON Collaborators; EMBRACE; GEMO; CIMBA.  Common breast cancer-predisposition alleles are associated with breast cancer risk in BRCA1 and BRCA2 mutation carriers. Am J Hum Genet. 2008;82(4):937-948.
PubMedArticle
41.
Andrieu  N, Easton  DF, Chang-Claude  J,  et al.  Effect of chest X-rays on the risk of breast cancer among BRCA1/2 mutation carriers in the International BRCA1/2 Carrier Cohort Study: a report from the EMBRACE, GENEPSO, GEO-HEBON, and IBCCS Collaborators’ Group. J Clin Oncol. 2006;24(21):3361-3366.
PubMedArticle
42.
Crosbie  EJ, Zwahlen  M, Kitchener  HC, Egger  M, Renehan  AG.  Body mass index, hormone replacement therapy, and endometrial cancer risk: a meta-analysis. Cancer Epidemiol Biomarkers Prev. 2010;19(12):3119-3130.
PubMedArticle
43.
Grzankowski  KS, Shimizu  DM, Kimata  C, Black  M, Terada  KY.  Clinical and pathologic features of young endometrial cancer patients with loss of mismatch repair expression. Gynecol Oncol. 2012;126(3):408-412.
PubMedArticle
44.
Joehlin-Price  AS, Perrino  CM, Stephens  J,  et al.  Mismatch repair protein expression in 1049 endometrial carcinomas, associations with body mass index, and other clinicopathologic variables. Gynecol Oncol. 2014;133(1):43-47.
PubMedArticle
45.
Huang  M, Djordjevic  B, Yates  MS,  et al.  Molecular pathogenesis of endometrial cancers in patients with Lynch syndrome. Cancer. 2013;119(16):3027-3033.
PubMedArticle
46.
Lu  KH, Schorge  JO, Rodabaugh  KJ,  et al.  Prospective determination of prevalence of Lynch syndrome in young women with endometrial cancer. J Clin Oncol. 2007;25(33):5158-5164.
PubMedArticle
×