Mathematical Models of Ovarian Cancer Incidence

A framework for assessing interactions for risk stratification models: the example of ovarian cancer

Generally, risk stratification models for cancer use effect estimates from risk/protective factor analyses that have not assessed potential interactions between these exposures. We have developed a 4-criterion framework for assessing interactions that includes statistical, qualitative, biological, and practical approaches. We present the application of this framework in an ovarian cancer setting because this is an important step in developing more accurate risk stratification models. Using data from 9 case-control studies in the Ovarian Cancer Association Consortium, we conducted a comprehensive analysis of interactions among 15 unequivocal risk and protective factors for ovarian cancer (including 14 non-genetic factors and a 36-variant polygenic score) with age and menopausal status. Pairwise interactions between the risk/protective factors were also assessed. We found that menopausal status modifies the association among endometriosis, first-degree family history of ovarian cancer, breastfeeding, and depot-medroxyprogesterone acetate use and disease risk, highlighting the importance of understanding multiplicative interactions when developing risk prediction models.

Lifetime ovulatory years and risk of epithelial ovarian cancer: a multinational pooled analysis

BACKGROUND

The role of ovulation in epithelial ovarian cancer (EOC) is supported by the consistent protective effects of parity and oral contraceptive use. Whether these factors protect through anovulation alone remains unclear. We explored the association between lifetime ovulatory years (LOY) and EOC.

METHODS

LOY was calculated using 12 algorithms. Odds ratios (ORs) and 95% confidence intervals (CIs) estimated the association between LOY or LOY components and EOC among 26 204 control participants and 21 267 case patients from 25 studies. To assess whether LOY components act through ovulation suppression alone, we compared beta coefficients obtained from regression models with expected estimates assuming 1 year of ovulation suppression has the same effect regardless of source.

RESULTS

LOY was associated with increased EOC risk (OR per year increase = 1.014, 95% CI = 1.009 to 1.020 to OR per year increase = 1.044, 95% CI = 1.041 to 1.048). Individual LOY components, except age at menarche, also associated with EOC. The estimated model coefficient for oral contraceptive use and pregnancies were 4.45 times and 12- to 15-fold greater than expected, respectively. LOY was associated with high-grade serous, low-grade serous, endometrioid, and clear cell histotypes (ORs per year increase = 1.054, 1.040, 1.065, and 1.098, respectively) but not mucinous tumors. Estimated coefficients of LOY components were close to expected estimates for high-grade serous but larger than expected for low-grade serous, endometrioid, and clear cell histotypes.

CONCLUSIONS

LOY is positively associated with nonmucinous EOC. Differences between estimated and expected model coefficients for LOY components suggest factors beyond ovulation underlie the associations between LOY components and EOC in general and for non-HGSOC.

Proliferation of the Fallopian Tube Fimbriae and Cortical Inclusion Cysts: Effects of the Menstrual Cycle and the Levonorgestrel Intrauterine Contraceptive System

BACKGROUND

The objectives of this study were (i) to explore whether differences in cell proliferation may help explain why most high-grade serous ovarian cancers (HGSOC) arise in the fallopian tube fimbriae (FTF) rather than in ovarian cortical inclusion cysts (CIC); (ii) to compare premenopausal and postmenopausal FTF proliferation as a reason why the age incidence of HGSOC increases at a slower rate after menopause; and (iii) to compare FTF proliferation in cycling women and women using the levonorgestrel intrauterine contraceptive system (Lng-IUS) to see whether proliferation on the Lng-IUS was lower.

METHODS

We studied 60 women undergoing a salpingo-oophorectomy. We used Ki67, paired-box gene 8 (PAX8, Müllerian marker), and calretinin (mesothelial marker) to study FTF and CIC proliferation.

RESULTS

FTF Ki67%+ was greater in the follicular than in the luteal phase (4.9% vs. 1.5%; P = 0.003); postmenopausal Ki67%+ was 1.7%. Ki67%+ in PAX8 negative (PAX8-) CICs was extremely low. Proliferation in PAX8+ CICs did not vary by menstrual phase or menopausal status. Follicular Ki67%+ was 2.6-fold higher in FTF than PAX8+ CICs. FTF Ki67%+ from 10 women using the Lng-IUS was not lower than in cycling women.

CONCLUSIONS

Overall FTF Ki67%+ is greater than overall CIC Ki67%+. Overall FTF Ki67%+ in postmenopausal women is lower than in premenopausal women. The Lng-IUS is not associated with lower FTF Ki67%+.

IMPACT

Ki67%+ provides an explanation of the preponderance of FTF-derived HGSOCs, and of the slower increase of HGSOCs after menopause. The Lng-IUS may not be associated with a protective effect against HGSOCs.

Comprehensive epithelial tubo-ovarian cancer risk prediction model incorporating genetic and epidemiological risk factors

BACKGROUND

Epithelial tubo-ovarian cancer (EOC) has high mortality partly due to late diagnosis. Prevention is available but may be associated with adverse effects. A multifactorial risk model based on known genetic and epidemiological risk factors (RFs) for EOC can help identify women at higher risk who could benefit from targeted screening and prevention.

METHODS

We developed a multifactorial EOC risk model for women of European ancestry incorporating the effects of pathogenic variants (PVs) in BRCA1, BRCA2, RAD51C, RAD51D and BRIP1, a Polygenic Risk Score (PRS) of arbitrary size, the effects of RFs and explicit family history (FH) using a synthetic model approach. The PRS, PV and RFs were assumed to act multiplicatively.

RESULTS

Based on a currently available PRS for EOC that explains 5% of the EOC polygenic variance, the estimated lifetime risks under the multifactorial model in the general population vary from 0.5% to 4.6% for the first to 99th percentiles of the EOC risk distribution. The corresponding range for women with an affected first-degree relative is 1.9%-10.3%. Based on the combined risk distribution, 33% of RAD51D PV carriers are expected to have a lifetime EOC risk of less than 10%. RFs provided the widest distribution, followed by the PRS. In an independent partial model validation, absolute and relative 5-year risks were well calibrated in quintiles of predicted risk.

CONCLUSION

This multifactorial risk model can facilitate stratification, in particular among women with FH of cancer and/or moderate-risk and high-risk PVs. The model is available via the CanRisk Tool (www.canrisk.org).

Lifetime ovulations and epithelial ovarian cancer risk and survival: A systematic review and meta-analysis

OBJECTIVE

To assess the relationship between lifetime ovulatory years (LOY) and Epithelial ovarian cancer (EOC) risk and survival.

METHODS

A systematic review was performed in accordance with PRISMA guidelines. Relevant studies were identified from PubMed, MEDLINE, and Embase through December 31, 2021 combining the following search: [("ovulation" or "ovulation cycles" or "ovulatory age" or "ovulatory cycles") and ("ovarian cancer" or "ovarian neoplasms") and ("humans" and "female")]. Reference lists of identified articles were searched for additional studies. Studies were excluded from consideration if they were not a published, peer-review article; not in English; lacked data on effect sizes; had data included in another publication; or were a review article, cross-sectional study, or case report. Two independent investigators screened abstracts and full texts for eligibility, extracted study-level data, and assigned study quality. Disagreements between abstractors were discussed and resolved by consensus.

RESULTS

Thirty-one reports were included in the qualitative review of LOY and EOC risk, inclusive of 24 studies with sufficient data to be included in the meta-analysis. Women with the highest level of LOY had 2.26 times higher odds of EOC than women with the lowest level of LOY (95% CI 1.94-2.83). LOY was associated with risk of serous (pooled OR 2.31, 95% CI 1.60-3.33) and endometrioid tumors (pooled OR 3.05, 95% CI 2.08-4.45) but not mucinous disease (pooled OR 1.52, 95% CI 0.87-2.64). There were only four studies examining the LOY-survival association, which precluded a quantitative assessment; however, three of the published studies reported worse outcome with greater LOY.

CONCLUSION

LOY is a risk factor for specific EOC histotypes and may also influences EOC survival. Standard definitions of LOY, participant-level data, and larger sample size will enable more precise quantitation of the LOY-EOC association, which can inform EOC risk assessment models.

Risk Model in Women with Ovarian Cancer Without Mutations

Ovarian cancer is characterised by the greatest mortality among all tumors of the reproductive tract. This study included 246 patients which consisted of 136 women with ovarian cancer without genetic mutation and 110 women with benign ovarian cysts. We created two mathematical logic models containing positive and negative risk factors of ovarian cancer such as: age at last menstruation cycle, patient age, OC, HRT, smoking, education status, and alcohol consumption. The calculated cut-off point for the first model was 0.5117. Classification determined on the basis of that cut-off point yielded 87.19% of correctly classified cases, of which 91.38% are "case" and 81.61% - "noncase". For the second model the designated cut-off point was set at 0.5149 and the percentage of correctly classified patients was 88.12%, with 92.24% correctly rated as cancer patients and 82.56% of the cases rightly recognised as having no ovarian cancer. Logit is a simple mathematical model that can be a useful tool for identification of patients with increased risk of ovarian cancer.

Practice Bulletin No 182: Hereditary Breast and Ovarian Cancer Syndrome

Hereditary breast and ovarian cancer syndrome is an inherited cancer-susceptibility syndrome characterized by multiple family members with breast cancer, ovarian cancer, or both. Based on the contemporary understanding of the origins and management of ovarian cancer and for simplicity in this document, ovarian cancer also refers to fallopian tube cancer and primary peritoneal cancer. Clinical genetic testing for gene mutations allows more precise identification of those women who are at an increased risk of inherited breast cancer and ovarian cancer. For these individuals, screening and prevention strategies can be instituted to reduce their risks. Obstetrician-gynecologists play an important role in the identification and management of women with hereditary breast and ovarian cancer syndrome. If an obstetrician-gynecologist or other gynecologic care provider does not have the necessary knowledge or expertise in cancer genetics to counsel a patient appropriately, referral to a genetic counselor, gynecologic or medical oncologist, or other genetics specialist should be considered (1). More genes are being discovered that impart varying risks of breast cancer, ovarian cancer, and other types of cancer, and new technologies are being developed for genetic testing. This Practice Bulletin focuses on the primary genetic mutations associated with hereditary breast and ovarian cancer syndrome, BRCA1 and BRCA2, but also will briefly discuss some of the other genes that have been implicated.

Epidemiology of ovarian cancer: a review

Ovarian cancer (OC) is the seventh most commonly diagnosed cancer among women in the world and the tenth most common in China. Epithelial OC is the most predominant pathologic subtype, with five major histotypes that differ in origination, pathogenesis, molecular alterations, risk factors, and prognosis. Genetic susceptibility is manifested by rare inherited mutations with high to moderate penetrance. Genome-wide association studies have additionally identified 29 common susceptibility alleles for OC, including 14 subtype-specific alleles. Several reproductive and hormonal factors may lower risk, including parity, oral contraceptive use, and lactation, while others such as older age at menopause and hormone replacement therapy confer increased risks. These associations differ by histotype, especially for mucinous OC, likely reflecting differences in etiology. Endometrioid and clear cell OC share a similar, unique pattern of associations with increased risks among women with endometriosis and decreased risks associated with tubal ligation. OC risks associated with other gynecological conditions and procedures, such as hysterectomy, pelvic inflammatory disease, and polycystic ovarian syndrome, are less clear. Other possible risk factors include environmental and lifestyle factors such as asbestos and talc powder exposures, and cigarette smoking. The epidemiology provides clues on etiology, primary prevention, early detection, and possibly even therapeutic strategies.

Epidemiology of ovarian cancer: a review

Ovarian cancer (OC) is the seventh most commonly diagnosed cancer among women in the world and the tenth most common in China. Epithelial OC is the most predominant pathologic subtype, with five major histotypes that differ in origination, pathogenesis, molecular alterations, risk factors, and prognosis. Genetic susceptibility is manifested by rare inherited mutations with high to moderate penetrance. Genome-wide association studies have additionally identified 29 common susceptibility alleles for OC, including 14 subtype-specific alleles. Several reproductive and hormonal factors may lower risk, including parity, oral contraceptive use, and lactation, while others such as older age at menopause and hormone replacement therapy confer increased risks. These associations differ by histotype, especially for mucinous OC, likely reflecting differences in etiology. Endometrioid and clear cell OC share a similar, unique pattern of associations with increased risks among women with endometriosis and decreased risks associated with tubal ligation. OC risks associated with other gynecological conditions and procedures, such as hysterectomy, pelvic inflammatory disease, and polycystic ovarian syndrome, are less clear. Other possible risk factors include environmental and lifestyle factors such as asbestos and talc powder exposures, and cigarette smoking. The epidemiology provides clues on etiology, primary prevention, early detection, and possibly even therapeutic strategies.

Epidemiology of ovarian cancer: a review

Ovarian cancer (OC) is the seventh most commonly diagnosed cancer among women in the world and the tenth most common in China. Epithelial OC is the most predominant pathologic subtype, with five major histotypes that differ in origination, pathogenesis, molecular alterations, risk factors, and prognosis. Genetic susceptibility is manifested by rare inherited mutations with high to moderate penetrance. Genome-wide association studies have additionally identified 29 common susceptibility alleles for OC, including 14 subtype-specific alleles. Several reproductive and hormonal factors may lower risk, including parity, oral contraceptive use, and lactation, while others such as older age at menopause and hormone replacement therapy confer increased risks. These associations differ by histotype, especially for mucinous OC, likely reflecting differences in etiology. Endometrioid and clear cell OC share a similar, unique pattern of associations with increased risks among women with endometriosis and decreased risks associated with tubal ligation. OC risks associated with other gynecological conditions and procedures, such as hysterectomy, pelvic inflammatory disease, and polycystic ovarian syndrome, are less clear. Other possible risk factors include environmental and lifestyle factors such as asbestos and talc powder exposures, and cigarette smoking. The epidemiology provides clues on etiology, primary prevention, early detection, and possibly even therapeutic strategies.

A GPS-Based Methodology to Analyze Environment-Health Associations at the Trip Level: Case-Crossover Analyses of Built Environments and Walking

Environmental health studies have examined associations between context and health with individuals as statistical units. However, investigators have been unable to investigate momentary exposures, and such studies are often vulnerable to confounding from, for example, individual-level preferences. We present a Global Positioning System (GPS)-based methodology for segmenting individuals' observation periods into visits to places and trips, enabling novel life-segment investigations and case-crossover analysis for improved inferences. We analyzed relationships between built environments and walking in trips. Participants were tracked for 7 days with GPS receivers and accelerometers and surveyed with a Web-based mapping application about their transport modes during each trip (Residential Environment and Coronary Heart Disease (RECORD) GPS Study, France, 2012-2013; 6,313 trips made by 227 participants). Contextual factors were assessed around residences and the trips' origins and destinations. Conditional logistic regression modeling was used to estimate associations between environmental factors and walking or accelerometry-assessed steps taken in trips. In case-crossover analysis, the probability of walking during a trip was 1.37 (95% confidence interval: 1.23, 1.61) times higher when trip origin was in the fourth (vs. first) quartile of service density and 1.47 (95% confidence interval: 1.23, 1.68) times higher when trip destination was in the fourth (vs. first) quartile of service density. Green spaces at the origin and destination of trips were also associated with within-individual, trip-to-trip variations in walking. Our proposed approach using GPS and Web-based surveys enables novel life-segment epidemiologic investigations.

Risk Prediction for Epithelial Ovarian Cancer in 11 United States-Based Case-Control Studies: Incorporation of Epidemiologic Risk Factors and 17 Confirmed Genetic Loci

Previously developed models for predicting absolute risk of invasive epithelial ovarian cancer have included a limited number of risk factors and have had low discriminatory power (area under the receiver operating characteristic curve (AUC) < 0.60). Because of this, we developed and internally validated a relative risk prediction model that incorporates 17 established epidemiologic risk factors and 17 genome-wide significant single nucleotide polymorphisms (SNPs) using data from 11 case-control studies in the United States (5,793 cases; 9,512 controls) from the Ovarian Cancer Association Consortium (data accrued from 1992 to 2010). We developed a hierarchical logistic regression model for predicting case-control status that included imputation of missing data. We randomly divided the data into an 80% training sample and used the remaining 20% for model evaluation. The AUC for the full model was 0.664. A reduced model without SNPs performed similarly (AUC = 0.649). Both models performed better than a baseline model that included age and study site only (AUC = 0.563). The best predictive power was obtained in the full model among women younger than 50 years of age (AUC = 0.714); however, the addition of SNPs increased the AUC the most for women older than 50 years of age (AUC = 0.638 vs. 0.616). Adapting this improved model to estimate absolute risk and evaluating it in prospective data sets is warranted.

Assessing individual risk for high-risk colorectal adenoma at first-time screening colonoscopy

Assessing risk of colorectal adenoma at first-time colonoscopy that are of higher likelihood of developing advanced neoplasia during surveillance could help tailor first-line colorectal cancer screening. We developed prediction models for high-risk colorectal adenoma (at least one adenoma ≥1 cm, or with advanced histology, or ≥3 adenomas) among 4,881 asymptomatic white men and 17,970 women who underwent colonoscopy as their first-time screening for colorectal cancer in two prospective US studies using logistic regressions. C-statistics and Hosmer-Lemeshow tests were used to evaluate discrimination and calibration. Ten-fold cross-validation was used for internal validation. A total of 330 (6.7%) men and 678 (3.8%) women were diagnosed with high-risk adenoma at first-time screening colonoscopy. The model for men included age, family history of colorectal cancer, BMI, smoking, sitting watching TV/VCR, regular aspirin/NSAID use, physical activity, and a joint term of multivitamin and alcohol. For women, the model included age, family history of colorectal cancer, BMI, smoking, alcohol, beef/pork/lamb as main dish, regular aspirin/NSAID, calcium, and oral contraceptive use. The C-statistic of the model for men was 0.67 and 0.60 for women (0.64 and 0.57 in cross-validation). Both models calibrated well. The predicted risk of high-risk adenoma for men in the top decile was 15.4% vs. 1.8% for men in the bottom decile (Odds Ratio [OR] = 9.41), and 6.6% vs. 2.1% for women (OR = 3.48). In summary, we developed and internally validated an absolute risk assessment tool for high-risk colorectal adenoma among the US population that may provide guidance for first-time colorectal cancer screening.

An epidemiologic risk prediction model for ovarian cancer in Europe: the EPIC study

BACKGROUND

Ovarian cancer has a high case-fatality ratio, largely due to late diagnosis. Epidemiologic risk prediction models could help identify women at increased risk who may benefit from targeted prevention measures, such as screening or chemopreventive agents.

METHODS

We built an ovarian cancer risk prediction model with epidemiologic risk factors from 202,206 women in the European Prospective Investigation into Cancer and Nutrition study.

RESULTS

Older age at menopause, longer duration of hormone replacement therapy, and higher body mass index were included as increasing ovarian cancer risk, whereas unilateral ovariectomy, longer duration of oral contraceptive use, and higher number of full-term pregnancies were decreasing risk. The discriminatory power (overall concordance index) of this model, as examined with five-fold cross-validation, was 0.64 (95% confidence interval (CI): 0.57, 0.70). The ratio of the expected to observed number of ovarian cancer cases occurring in the first 5 years of follow-up was 0.90 (293 out of 324, 95% CI: 0.81-1.01), in general there was no evidence for miscalibration.

CONCLUSION

Our ovarian cancer risk model containing only epidemiological data showed modest discriminatory power for a Western European population. Future studies should consider adding informative biomarkers to possibly improve the predictive ability of the model.

A melanoma risk score in a Brazilian population

BACKGROUND

Important risk factors for cutaneous melanoma (CM) are recognized, but standardized scores for individual assessment must still be developed.

OBJECTIVES

The objective of this study was to develop a risk score of CM for a Brazilian sample.

METHODS

To verify the estimates of the main risk factors for melanoma, derived from a meta-analysis (Italian-based study), and externally validate them in a population in southern Brazil by means of a case-control study. A total of 117 individuals were evaluated. Different models were constructed combining the summary coefficients of different risk factors, derived from the meta-analysis, multiplied by the corresponding category of each variable for each participant according to a mathematical expression.

RESULTS

the variable that best predicted the risk of CM in the studied population was hair color (AUC: 0.71; 95% CI: 0.62-0.79). Other important factors were freckles, sunburn episodes, and skin and eye color. Consideration of other variables such as common nevi, elastosis, family history, and premalignant lesions did not improve the predictive ability of the models.

CONCLUSION

The discriminating capacity of the proposed model proved to be superior or comparable to that of previous risk models proposed for CM.

Risk prediction for breast, endometrial, and ovarian cancer in white women aged 50 y or older: derivation and validation from population-based cohort studies

BACKGROUND

Breast, endometrial, and ovarian cancers share some hormonal and epidemiologic risk factors. While several models predict absolute risk of breast cancer, there are few models for ovarian cancer in the general population, and none for endometrial cancer.

METHODS AND FINDINGS

Using data on white, non-Hispanic women aged 50+ y from two large population-based cohorts (the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial [PLCO] and the National Institutes of Health-AARP Diet and Health Study [NIH-AARP]), we estimated relative and attributable risks and combined them with age-specific US-population incidence and competing mortality rates. All models included parity. The breast cancer model additionally included estrogen and progestin menopausal hormone therapy (MHT) use, other MHT use, age at first live birth, menopausal status, age at menopause, family history of breast or ovarian cancer, benign breast disease/biopsies, alcohol consumption, and body mass index (BMI); the endometrial model included menopausal status, age at menopause, BMI, smoking, oral contraceptive use, MHT use, and an interaction term between BMI and MHT use; the ovarian model included oral contraceptive use, MHT use, and family history or breast or ovarian cancer. In independent validation data (Nurses' Health Study cohort) the breast and ovarian cancer models were well calibrated; expected to observed cancer ratios were 1.00 (95% confidence interval [CI]: 0.96-1.04) for breast cancer and 1.08 (95% CI: 0.97-1.19) for ovarian cancer. The number of endometrial cancers was significantly overestimated, expected/observed = 1.20 (95% CI: 1.11-1.29). The areas under the receiver operating characteristic curves (AUCs; discriminatory power) were 0.58 (95% CI: 0.57-0.59), 0.59 (95% CI: 0.56-0.63), and 0.68 (95% CI: 0.66-0.70) for the breast, ovarian, and endometrial models, respectively.

CONCLUSIONS

These models predict absolute risks for breast, endometrial, and ovarian cancers from easily obtainable risk factors and may assist in clinical decision-making. Limitations are the modest discriminatory ability of the breast and ovarian models and that these models may not generalize to women of other races. Please see later in the article for the Editors' Summary.

Using multiple risk models with preventive interventions

An ideal preventive intervention would have negligible side effects and could be applied to the entire population, thus achieving maximal preventive impact. Unfortunately, many interventions have adverse effects and beneficial effects. For example, tamoxifen reduces the risk of breast cancer by about 50% and the risk of hip fracture by 45%, but increases the risk of stroke by about 60%; other serious adverse effects include endometrial cancer and pulmonary embolus. Hence, tamoxifen should only be given to the subset of the population with high enough risks of breast cancer and hip fracture such that the preventive benefits outweigh the risks. Recommendations for preventive use of tamoxifen have been based primarily on breast cancer risk. Age-specific and race-specific rates were considered for other health outcomes, but not risk models. In this paper, we investigate the extent to which modeling not only the risk of breast cancer, but also the risk of stroke, can improve the decision to take tamoxifen. These calculations also give insight into the relative benefits of improving the discriminatory accuracy of such risk models versus improving the preventive effectiveness or reducing the adverse risks of the intervention. Depending on the discriminatory accuracies of the risk models, there may be considerable advantage to modeling the risks of more than one health outcome.

Age at menopause: imputing age at menopause for women with a hysterectomy with application to risk of postmenopausal breast cancer

PURPOSE

Age at menopause, a major marker in the reproductive life, may bias results for evaluation of breast cancer risk after menopause.

METHODS

We followed 38,948 premenopausal women in 1980 and identified 2,586 who reported hysterectomy without bilateral oophorectomy and 31,626 who reported natural menopause during 22 years of follow-up. We evaluated risk factors for natural menopause, imputed age at natural menopause for women reporting a hysterectomy without bilateral oophorectomy, and estimated the hazard of reaching natural menopause in the next 2 years. We applied this imputed age at menopause to both increase sample size and to evaluate the relation between postmenopausal exposures and risk of breast cancer.

RESULTS

Age, cigarette smoking, age at menarche, pregnancy history, body mass index, history of benign breast disease, and history of breast cancer were each significantly related to age at natural menopause; duration of oral contraceptive use and family history of breast cancer were not. The imputation increased sample size substantially, and although some risk factors after menopause were weaker in the expanded model (height, and alcohol use), use of hormone therapy is less biased.

CONCLUSIONS

Imputing age at menopause increases sample size, broadens generalizability making it applicable to women with hysterectomy, and reduces bias.

10-Year risk of colorectal cancer: development and validation of a prediction model in middle-aged Japanese men

BACKGROUND

To estimate an individual's probability of developing colorectal cancer (CRC) may aid health professionals and individuals in improving lifestyle behaviors or deciding the screening regimens. As fewer studies on cancer risk prediction were seen so far, we initially developed an assessment tool with synthesizing key information from a variety of CRC risk factors through a large population-based cohort study.

METHOD

The prediction model was derived from 28,115 men in the Japan Public Health Center-based (JPHC) Prospective Study Cohort II (follow-up: 1993-2005), with risk factors selected by Cox proportion hazard regression. 18,256 men in the JPHC Study Cohort I (follow-up: 1995-2005) were used to evaluate the model's performance.

RESULTS

543 and 398 CRCs were diagnosed during the follow-up period in Cohorts II and I, respectively. The prediction model, including age, BMI, alcohol consumption, smoking status, and the daily physical activity level, showed modest discrimination ability for CRC (C=0.70; 95% confidential interval, 0.68-0.72) in Cohort II and well calibrated in Cohort I (Hosmer-Lemeshow χ(2)=14.2, P=0.08).

CONCLUSION

The 10-year CRC risk prediction model may be used to estimate CRC risk in Japanese men. It may also play a role in the promotion of CRC prevention strategies.

Anti-MUC1 antibodies and ovarian cancer risk: prospective data from the Nurses' Health Studies

BACKGROUND

The surface epithelial glycoprotein MUC1 becomes overexpressed and hypoglycosylated in adenocarcinomas; similar changes occur during nonmalignant inflammatory events. Antibodies developed against tumor-like MUC1 in response to such events could be one way through which ovarian cancer risk factors operate.

METHODS

We evaluated the association between anti-MUC1 antibodies and risk of ovarian cancer in a prospective nested case-control study in the Nurses' Health Studies. We used an ELISA to measure plasma anti-MUC1 antibodies in 117 ovarian cancer cases collected at least 3 years before diagnosis and 339 matched controls.

RESULTS

In controls, younger women (P-trend = 0.03), those with a tubal ligation (P = 0.03), and those with fewer ovulatory cycles (P-trend = 0.04) had higher antibody levels. In cases, women with late-stage disease (P = 0.04) and those whose specimen was >11 years remote from diagnosis (P = 0.01) had higher antibody levels. Overall, increasing anti-MUC1 antibody levels were associated with a nonsignificant trend for lower risk for ovarian cancer, but there was highly significant heterogeneity by age (P-heterogeneity = 0.005). In women <64 years, the antibody level in quartiles 2 to 4 versus quartile 1 were associated with reduced risk (relative risk = 0.53; 95% confidence interval, 0.31-0.93; P-trend = 0.03), whereas in women > or = 64 years, the corresponding relative risk was 2.11 (95% confidence interval, 0.73-6.04); P-trend = 0.05).

CONCLUSION

Anti-MUC1 antibodies evaluated several years before diagnosis may be associated with lower risk of subsequent ovarian cancer in women <64 years old at assessment.

IMPACT

Key elements of an "immune model" to explain ovarian cancer risk factors are confirmed and should be evaluated in larger prospective studies.

Cumulative risk of colon cancer up to age 70 years by risk factor status using data from the Nurses' Health Study

The authors developed a comprehensive model of colon cancer incidence that allows for nonproportional hazards and accounts for the temporal nature of risk factors. They estimated relative risk based on cumulative incidence of colon cancer by age 70 years. Using multivariate, nonlinear Poisson regression, they determined colon cancer risk among 83,767 participants in the Nurses' Health Study. The authors observed 701 cases of colon cancer between 1980 and June 1, 2004. There was increased risk for a positive family history of colon or rectal cancer (55%), 10 or more pack-years of cigarette smoking before age 30 years (16%), and tallness (67 inches (170 cm) vs. 61 inches (155 cm): 19%). Reduced risk was observed for current postmenopausal hormone use (-23%), being physically active (21 metabolic equivalent (MET)-hours/week vs. 2 MET-hours/week: -49%), taking aspirin (7 tablets/week vs. none: -29%), and being screened (-24%). Women who smoked, had a consistently high relative weight, had a low physical activity level, consumed red or processed meat daily, were never screened, and consumed low daily amounts of folate had almost a 4-fold higher cumulative risk of colon cancer by age 70 years. For women with a high risk factor profile, adopting a healthier lifestyle could dramatically reduce colon cancer risk.

Timing of births and endometrial cancer risk in Swedish women

While a protective long-term effect of parity on endometrial cancer risk is well established, the impact of timing of births is not fully understood. We examined the relationship between endometrial cancer risk and reproductive characteristics in a population-based cohort of 2,674,465 Swedish women, 20-72 years of age. During follow-up from 1973 to 2004, 7,386 endometrial cancers were observed. Compared to uniparous women, nulliparous women had a significantly elevated endometrial cancer risk (hazard ratio [HR] = 1.32, 95% confidence interval [CI], 1.22-1.42). Endometrial cancer risk decreased with increasing parity; compared to uniparous women, women with > or =4 births had a HR = 0.66 (95% CI, 0.59-0.74); p-trend < 0.001. Among multiparous women, we observed no relationship of risk with age at first birth after adjustment for other reproductive factors. While we initially observed a decreased risk with later ages at last birth, this appeared to reflect a stronger relationship with time since last birth, with women with shorter times being at lowest risk. In models for multiparous women that included number of births, age at first and last birth, and time since last birth, age at last birth was not associated with endometrial cancer risk, while shorter time since last birth and increased parity were associated with statistically significantly reduced endometrial cancer risks. The HR was 3.95 (95% CI; 2.17-7.20; p-trend = <0.0001) for women with > or =25 years since a last birth compared to women having given birth within 4 years. Our findings support that clearance of initiated cells during delivery may be important in endometrial carcinogenesis.

Validation of a colorectal cancer risk prediction model among white patients age 50 years and older

PURPOSE

Validation of an absolute risk prediction model for colorectal cancer (CRC) by using a large, population-based cohort.

PATIENTS AND METHODS

The National Institutes of Health (NIH) -American Association of Retired Persons (AARP) diet and health study, a prospective cohort study, was used to validate the model. Men and women age 50 to 71 years at baseline answered self-administered questionnaires that asked about demographic characteristics, diet, lifestyle, and medical histories. We compared expected numbers of CRC patient cases predicted by the model to the observed numbers of CRC patient cases identified in the NIH-AARP study overall and in subgroups defined by risk factor combinations. The discriminatory power was measured by the area under the receiver-operating characteristic curve (AUC).

RESULTS

During an average of 6.9 years of follow-up, we identified 2,092 and 832 incident CRC patient cases in men and women, respectively. The overall expected/observed ratio was 0.99 (95% CI, 0.95 to 1.04) in men and 1.05 (95% CI, 0.98 to 1.11) in women. Agreement between the expected and the observed number of cases was good in most risk factor categories, except for in subgroups defined by CRC screening and polyp history. This discrepancy may be caused by differences in the question on screening and polyp history between two studies. The AUC was 0.61 (95% CI, 0.60 to 0.62) for men and 0.61 (95% CI, 0.59 to 0.62) for women, which was similar to other risk prediction models.

CONCLUSION

The absolute risk model for CRC was well calibrated in a large prospective cohort study. This prediction model, which estimates an individual's risk of CRC given age and risk factors, may be a useful tool for physicians, researchers, and policy makers.

Criteria for the evaluation of large cohort studies: an application to the nurses' health study

Evaluating the success of major funding programs from the National Institutes of Health (NIH) remains a vexing challenge. We propose a set of criteria to evaluate epidemiological studies that fit within the discovery, development, and delivery paradigm introduced by the NIH. We apply these criteria to the Nurses' Health Study (NHS), a large epidemiological cohort study initiated in the 1970s to evaluate the associations between oral contraceptives and risk of breast cancer and between diet and other lifestyle factors and risk of cancer overall. Our evaluation suggests that the NHS has led to important changes in health practice, and it underscores the need to develop metrics that are suitable to the evaluation of large epidemiological cohort studies.

Opportunities and challenges in ovarian cancer research, a perspective from the 11th Ovarian cancer action/HHMT Forum, Lake Como, March 2007

Advances in surgery and chemotherapy have improved the 5-year survival for patients with epithelial ovarian cancer, but have not impacted on the ultimate rate of cure in a disease that is diagnosed in late stage and that recurs in the majority of patients. "Omic" technologies promise to define genetically driven aberrant signaling pathways in malignant cells, provided that bioinformatic expertise can be focused on a cancer that is neither common nor rare. Molecular therapeutics must be linked to molecular diagnostics to permit individualized therapy. Not only epithelial cancer cells but also stroma, vasculature and the immune response must be targeted. Closer collaboration between academic institutions, biotech and pharma will be required to facilitate this process and to interest the private sector in an orphan disease. New preclinical models may permit more efficient development of drugs and siRNA that can target dormant drug resistant stem cells. Strategies must be developed to deal with the heterogeneity of different grades and histotypes. Identification of women at increased risk will facilitate prevention and early detection in subsets of patients. BRCA1/2 might be sequenced in all ovarian cancer patients to identify new kindreds. Epidemiologic algorithms are being developed and validated. Awareness must be raised that oral contraceptives can reduce risk of developing ovarian cancer by 50%. Early detection is likely to require panels of complementary biomarkers, analyzed by sophisticated statistical techniques, to improve sensitivity while maintaining extremely high specificity. As ovarian cancer becomes a chronic disease, greater emphasis will be placed on the challenges facing survivors.

Risk assessment models to estimate cancer probabilities

Cancer risk has become a significant research topic due to an increase in statistical risk models built to predict cancer incidence or mortality. Over the past 3 years, 15 models on the development of different types of cancer, including breast, colorectal, prostate, gastric, lung, ovarian, pancreatic, testicular, and skin, have been published. Risk assessment models are dynamic; they need to be updated as often as risks are discovered or changed. Not only are cancer risk models challenging to build, but, due to literacy-related issues, the cancer risk itself is challenging to communicate to the public. Clearly, guidelines outlining how to create valid and reliable risk assessment models are needed.

A Prospective Study of the Transient Decrease in Ovarian Cancer Risk Following Childbirth

Epidemiologic evidence shows that the risk of ovarian cancer is decreased following childbirth. We examined the time points when the decreased risk of postpartum maternal ovarian cancer reaches the lowest point and whether the protective effect diminishes over time. A case-control study nested within the Swedish Fertility Register included 10,086 cases of epithelial ovarian cancer recorded in the Swedish Cancer Register from 1961 to 2001. From the Fertility Register, 49,249 eligible subjects matched to the cases by age were selected as controls. The analysis contrasted risk between adjacent parities through logistic regression models that included indicator variables representing each year of age, age at delivery, and time since delivery. Compared with nulliparous women, uniparous women had a transient decrease in maternal ovarian cancer risk at 2 years after delivery (spline-derived odds ratio, 0.71; 95% confidence interval, 0.53-0.95, for those delivered at age 25 years) and maintained a lower risk for 4 years postpartum. Similar transient decreases were observed in biparous women compared with uniparous women and in women with three parities compared with biparous women. The protective effect of childbearing seemed to diminish with time. The transient decrease in postpartum ovarian cancer risk may define the latent period required for pregnancy hormones in clearing out ovarian cells that have undergone early stages of malignant transformation. The period before the risk increases again could indicate the period required for ovarian cancer induction.

Paracetamol use and risk of ovarian cancer: a meta-analysis

AIM

Ovarian cancer remains the most fatal gynaecological malignancy. Several observational studies have examined paracetamol as a potential chemopreventive agent. The nonconclusive nature of the epidemiological evidence prompted us to conduct a detailed meta-analysis of the studies published on the subject in peer-reviewed literature.

METHODS

A comprehensive search for articles published up to 2004 was performed, reviews of each study were conducted and data were abstracted. Prior to meta-analysis, the studies were evaluated for publication bias and heterogeneity. Pooled relative risk estimates (RR) and 95% confidence intervals (CIs) were calculated using the random and the fixed-effects models.

RESULTS

Eight studies (four case-control and four cohort studies), published between 1998 and 2004, were included. We found no evidence of publication bias or heterogeneity among the studies. The analysis revealed an inverse association between paracetamol use and ovarian cancer risk. This association was marginally significant assuming a random-effects model (RR=0.84, 95% CI 0.70, 1.00), but not statistically significant assuming a fixed-effects model (RR=0.90, 95% CI 0.80, 1.01). When the analysis was stratified into subgroups according to study design, the association was inverse in both case-control and cohort studies, but only in the former was it statistically significant. The sensitivity analysis strengthened our confidence in the validity of this association. Furthermore, our results provided evidence for a dose effect; 'regular use' was associated with a statistically significant 30% reduction in the risk of developing ovarian cancer compared with non-use (RR=0.70, 95% CI 0.51, 0.95).

CONCLUSIONS

Our meta-analysis supports a protective association between paracetamol use and ovarian cancer, and provides evidence for a dose effect. However, the question of paracetamol's potential association with ovarian cancer deserves further verification, since proof of chemoprevention would represent a major public health advance.

Intake of folate and related nutrients in relation to risk of epithelial ovarian cancer

Assessments of the relation between folate intake and ovarian cancer risk have been limited and inconsistent. Therefore, the authors prospectively examined the association of dietary and supplemental intakes of folate, methionine, and vitamin B(6) with ovarian cancer risk among 80,254 Nurses' Health Study participants. Beginning in 1976, women completed biennial questionnaires assessing ovarian cancer risk factors; starting in 1980, food frequency questionnaires were administered every 2-4 years. During 22 years of follow-up (1980-2002), the authors confirmed 481 incident epithelial ovarian cancers. There were no associations between total folate (top quintile vs. bottom: relative risk (RR) = 1.21, 95% confidence interval (CI): 0.92, 1.60), methionine (RR = 1.00, 95% CI: 0.76, 1.33), dietary vitamin B(6) (RR = 1.09, 95% CI: 0.81, 1.47), or total vitamin B(6) (RR = 1.13, 95% CI: 0.85, 1.51) intake and ovarian cancer risk. Higher dietary folate was associated with a modestly decreased risk after exclusion of cases diagnosed during the 4 follow-up years after dietary assessment (RR = 0.66, 95% CI: 0.43, 1.03) and for the serous subtype (RR = 0.51, 95% CI: 0.31, 0.84). Results did not vary by alcohol intake, multivitamin use, menopausal status, or oral contraceptive use. There was little evidence that folate, methionine, and vitamin B(6) are important in ovarian cancer risk, although dietary folate was inversely associated with risk in some analyses.