Cigarette smoking is associated with adverse survival among women with ovarian cancer: Results from a pooled analysis of 19 studies

Lifetime Exposure to Cigarette Smoke, B-Cell Tumor Immune Infiltration, and Immunoglobulin Abundance in Ovarian Tumors

BACKGROUND

Cigarette smoke exposure has been linked to systemic immune dysfunction, including for B-cell and immunoglobulin (Ig) production, and poor outcomes in patients with ovarian cancer. No study has evaluated the impact of smoke exposure across the life-course on B-cell infiltration and Ig abundance in ovarian tumors.

METHODS

We measured markers of B and plasma cells and Ig isotypes using multiplex immunofluorescence on 395 ovarian cancer tumors in the Nurses' Health Study (NHS)/NHSII. We conducted beta-binomial analyses evaluating odds ratios (OR) and 95% confidence intervals (CI) for positivity of immune markers by cigarette exposure among cases and Cox proportional hazards models to evaluate hazard ratios (HR) and 95% CI for developing tumors with low (

RESULTS

There were no associations between smoke exposure and B-cell or IgM infiltration in ovarian tumors. Among cases, we observed higher odds of IgA+ among ever smokers (OR, 1.54; 95% CI, 1.14-2.07) and ever smokers with no parental smoke exposure (OR, 2.03; 95% CI, 1.18-3.49) versus never smokers. Women with parental cigarette smoke exposure versus not had higher risk of developing ovarian cancer with low IgG+ (HR, 1.51; 95% CI, 1.10-2.09), whereas ever versus never smokers had a lower risk (HR, 0.74; 95% CI, 0.56-0.99).

CONCLUSIONS

Ever smoking was associated with increased odds of IgA in ovarian tumors.

IMPACT

IgA has been associated with improved ovarian cancer outcomes, suggesting that although smoking is associated with poor outcomes in patients with ovarian cancer, it may lead to improved tumor immunogenicity.

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Key Words Collapse

MESH Headings

• Humans
• Female
• Ovarian Neoplasms/immunology
• Ovarian Neoplasms/pathology
• Ovarian Neoplasms/epidemiology
• Middle Aged
• Adult
• B-Lymphocytes/immunology
• Immunoglobulins/blood
• Lymphocytes, Tumor-Infiltrating/immunology
• Aged
• Cigarette Smoking/adverse effects
• Cigarette Smoking/immunology

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Grants

• P01 CA087969 NCI NIH HHS
• 9JK02 Florida Department of Health (DOH)
• UM1 CA186107 NCI NIH HHS
• P01 CA87969 National Cancer Institute (NCI)
• U01 CA232758 NCI NIH HHS
• U01 CA176726 NCI NIH HHS

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Affiliation(s)

Cassandra A Hathaway Department of Cancer Epidemiology, Moffitt Cancer Center, Tampa, Florida
Mary K Townsend Department of Cancer Epidemiology, Moffitt Cancer Center, Tampa, Florida
Tianyi Wang Department of Cancer Epidemiology, Moffitt Cancer Center, Tampa, Florida
Christine Vinci Department of Health Outcomes and Behavior, Moffitt Cancer Center, Tampa, Florida
Danielle E Jake-Schoffman Department of Health Education and Behavior, University of Florida, Gainesville, Florida
Jonathan L Hecht Department of Pathology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts
Daryoush Saeed-Vafa Department of Anatomic Pathology, Moffitt Cancer Center, Tampa, Florida Advanced Analytical and Digital Laboratory, Moffitt Cancer Center, Tampa, Florida
Carlos Moran Segura Advanced Analytical and Digital Laboratory, Moffitt Cancer Center, Tampa, Florida
Jonathan V Nguyen Advanced Analytical and Digital Laboratory, Moffitt Cancer Center, Tampa, Florida
Jose R Conejo-Garcia Department of Immunology, Duke University School of Medicine, Durham, North Carolina
Brooke L Fridley Department of Biostatistics and Bioinformatics, Moffitt Cancer Center, Tampa, Florida
Shelley S Tworoger Department of Cancer Epidemiology, Moffitt Cancer Center, Tampa, Florida Knight Cancer Institute and Division of Oncological Sciences, Oregon Health & Science University, Portland, Oregon

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The clinical impact of continued smoking in patients with breast and other hormone-dependent cancer: A systematic literature review

We conducted a systematic review of studies that investigated whether quitting smoking at or around diagnosis improves survival of patients with hormone-dependent cancers (HDC). Nine studies published in 2013-2022 were included. Studies were very diverse in terms of design, definition of quitters and continued smokers, and prevalence of prognostic factors other than smoking cessation (e.g. patients' demographics, tumour characteristic, and treatments). For breast, ovarian, and endometrial cancer, all included studies found that quitters had better overall, disease specific, and disease-free survival than continued smokers. For prostate cancer, there was no evidence of an association of smoking cessation with improved survival. This literature review provided suggestive evidence that female smokers diagnosed with cancer of the breast, ovary, or endometrium may improve their chances of surviving by stopping smoking. Smoking cessation counselling should become part of standard oncological care for these patients and integrated into breast cancer screening programs.

Predictors of residual disease after debulking surgery in advanced stage ovarian cancer

Objective

Optimal debulking with no macroscopic residual disease strongly predicts ovarian cancer survival. The ability to predict likelihood of optimal debulking, which may be partially dependent on tumor biology, could inform clinical decision-making regarding use of neoadjuvant chemotherapy. Thus, we developed a prediction model including epidemiological factors and tumor markers of residual disease after primary debulking surgery.

Methods

Univariate analyses examined associations of 11 pre-diagnosis epidemiologic factors (n=593) and 24 tumor markers (n=204) with debulking status among incident, high-stage, epithelial ovarian cancer cases from the Nurses' Health Studies and New England Case Control study. We used Bayesian model averaging (BMA) to develop prediction models of optimal debulking with 5x5-fold cross-validation and calculated the area under the curve (AUC).

Results

Current aspirin use was associated with lower odds of optimal debulking compared to never use (OR=0.52, 95%CI=0.31-0.86) and two tissue markers, ADRB2 (OR=2.21, 95%CI=1.23-4.41) and FAP (OR=1.91, 95%CI=1.24-3.05) were associated with increased odds of optimal debulking. The BMA selected aspirin, parity, and menopausal status as the epidemiologic/clinical predictors with the posterior effect probability ≥20%. While the prediction model with epidemiologic/clinical predictors had low performance (average AUC=0.49), the model adding tissue biomarkers showed improved, but weak, performance (average AUC=0.62).

Conclusions

Addition of ovarian tumor tissue markers to our multivariable prediction models based on epidemiologic/clinical data slightly improved the model performance, suggesting debulking status may be in part driven by tumor characteristics. Larger studies are warranted to identify those at high risk of poor surgical outcomes informing personalized treatment.

Racial disparities in epithelial ovarian cancer survival: An examination of contributing factors in the Ovarian Cancer in Women of African Ancestry consortium

Black women diagnosed with epithelial ovarian cancer have poorer survival compared to white women. Factors that contribute to this disparity, aside from socioeconomic status and guideline-adherent treatment, have not yet been clearly identified. We examined data from the Ovarian Cancer in Women of African Ancestry (OCWAA) consortium which harmonized data on 1074 Black women and 3263 white women with ovarian cancer from seven US studies. We selected potential mediators and confounders by examining associations between each variable with race and survival. We then conducted a sequential mediation analysis using an imputation method to estimate total, direct, and indirect effects of race on ovarian cancer survival. Black women had worse survival than white women (HR = 1.30; 95% CI 1.16-1.47) during study follow-up; 67.9% of Black women and 69.8% of white women died. In our final model, mediators of this disparity include college education, nulliparity, smoking status, body mass index, diabetes, diabetes/race interaction, postmenopausal hormone (PMH) therapy duration, PMH duration/race interaction, PMH duration/age interaction, histotype, and stage. These mediators explained 48.8% (SE = 12.1%) of the overall disparity; histotype/stage and PMH duration accounted for the largest fraction. In summary, nearly half of the disparity in ovarian cancer survival between Black and white women in the OCWAA consortium is explained by education, lifestyle factors, diabetes, PMH use, and tumor characteristics. Our findings suggest that several potentially modifiable factors play a role. Further research to uncover additional mediators, incorporate data on social determinants of health, and identify potential avenues of intervention to reduce this disparity is urgently needed.

Tobacco Smoking and Survival Following a Diagnosis with Ovarian Cancer

BACKGROUND

Little is known about the influence of smoking on ovarian cancer survival. We investigated this relationship in a hospital-based study.

METHODS

Analyses included 519 women with ovarian cancer. We used multivariable adjusted Cox proportional hazards regression models to estimate HRs and 95% confidence intervals (CI).

RESULTS

Risk of all-cause mortality was increased for current smokers (HR = 1.70; 95% CI: 1.09-2.63) versus never smokers, especially for those with ≥15 cigarettes per day (HR = 1.92; 95% CI: 1.15-3.20). Results were largely similar after additional adjustment for debulking status (current vs. never smokers, HR = 2.96; 95% CI: 1.07-8.21) or neoadjuvant chemotherapy (comparable HR = 2.87; 95% CI: 1.02-8.06). Compared with never smokers, smoking duration ≥20 years (HR = 1.38; 95% CI: 0.94-2.03) and ≥20 pack-years (HR = 1.35; 95% CI: 0.92-1.99) were suggestively associated with worse outcomes. Current smoking was also positively associated with the risk of mortality among patients with ovarian cancer recurrence (current vs. never/past smokers, HR = 2.79; 95% CI: 1.44-5.41), despite the null association between smoking and recurrence (HR = 1.46; 95% CI: 0.86-2.48). Furthermore, no association was observed for smoking initiation before age 18 (HR = 1.22; 95% CI: 0.80-1.85), or either environmental smoke exposure at home (HR = 1.16; 95% CI: 0.76-1.78) or at work (HR = 1.10; 95% CI: 0.75-1.60).

CONCLUSIONS

Our results suggest active tobacco smoking is associated with worse ovarian cancer outcomes, particularly after a recurrence.

IMPACT

Our findings support structured smoking cessation programs for patients with ovarian cancer, especially in recurrent settings. Further research to confirm these findings and examine the interplay between smoking and the tumor immune microenvironment may help provide insight into ovarian cancer etiology.

Germline BRCA variants, lifestyle and ovarian cancer survival

OBJECTIVE

Women with ovarian cancer who have a pathogenic germline variant in BRCA1 or BRCA2 (BRCA) have been shown to have better 5-year survival after diagnosis than women who are BRCA-wildtype (non-carriers). Modifiable lifestyle factors, including smoking, physical activity and body mass index (BMI) have previously been associated with ovarian cancer survival; however, it is unknown whether these associations differ by germline BRCA status.

METHODS

We investigated measures of lifestyle prior to diagnosis in two cohorts of Australian women with invasive epithelial ovarian cancer, using Cox proportional hazards regression to calculate adjusted hazard ratios (HRs) and 95% confidence intervals (CIs).

RESULTS

In the combined studies (n = 1923), there was little association between physical activity, BMI or alcohol intake and survival, and no difference by BRCA status. However, the association between current smoking status before diagnosis and poorer survival was stronger for BRCA variant carriers (HR 1.98; 95% CI 1.20-3.27) than non-carriers (HR 1.18; 95% CI 0.96-1.46; p-interaction 0.02). We saw a similar differential association with smoking when we pooled results from two additional cohorts from the USA and UK (n = 2120). Combining the results from all four studies gave a pooled-HR of 1.94 (95% CI 1.28-2.94) for current smoking among BRCA variant carriers compared to 1.08 (0.90-1.29) for non-carriers.

CONCLUSIONS

Our results suggest that the adverse effect of smoking on survival may be stronger for women with a BRCA variant than those without. Thus, while smoking cessation may improve outcomes for all women with ovarian cancer, it might provide a greater benefit for BRCA variant carriers.

Reproductive Factors Do Not Influence Survival with Ovarian Cancer

BACKGROUND

Previous studies on the association between reproductive factors and ovarian cancer survival are equivocal, possibly due to small sample sizes.

METHODS

Using data on 11,175 people diagnosed with primary invasive epithelial ovarian, fallopian tube, or primary peritoneal cancer (ovarian cancer) from 16 studies in the Ovarian Cancer Association Consortium (OCAC), we examined the associations between survival and age at menarche, combined oral contraceptive use, parity, breastfeeding, age at last pregnancy, and menopausal status using Cox proportional hazard models. The models were adjusted for age at diagnosis, race/ethnicity, education level, and OCAC study and stratified on stage and histotype.

RESULTS

During the mean follow-up of 6.34 years (SD = 4.80), 6,418 patients passed away (57.4%). There was no evidence of associations between the reproductive factors and survival among patients with ovarian cancer overall or by histotype.

CONCLUSIONS

This study found no association between reproductive factors and survival after an ovarian cancer diagnosis.

IMPACT

Reproductive factors are well-established risk factors for ovarian cancer, but they are not associated with survival after a diagnosis of ovarian cancer.

A Novel Mixed Methods Approach Combining Geospatial Mapping and Qualitative Inquiry to Identify Multilevel Policy Targets: The Focused Rapid Assessment Process (fRAP) Applied to Cancer Survivorship

Multi-level perspectives across communities, medical systems and policy environments are needed, but few methods are available for health services researchers with limited resources. We developed a mixed method health policy approach, the focused Rapid Assessment Process (fRAP), that is designed to uncover multi-level modifiable barriers and facilitators contributing to public health issues. We illustrate with a study applying fRAP to the issue of cancer survivorship care. Through this multi-level investigation we identified two major modifiable areas impacting high-quality cancer survivorship care: 1) the importance of cancer survivorship guidelines/data, 2) the need for improved oncology-primary care relationships. This article contributes to the mixed methods literature by coupling geospatial mapping to qualitative rapid assessment to efficiently identify policy change targets.

Ovarian cancer survival by stage, histotype, and pre-diagnostic lifestyle factors, in the prospective UK Million Women Study

BACKGROUND

Ovarian cancer is the fifth leading cause of cancer mortality in UK women. Ovarian cancer survival varies by disease stage at diagnosis, but evidence is mixed on the effect of tumour histological type (histotype) and other factors.

METHODS

1.3 million UK women completed a detailed health questionnaire in 1996-2001 and were followed for incident cancers and deaths via linkage to national databases. Using Cox regression models, we estimated adjusted relative risks (RRs) of death from ovarian cancer, by stage at diagnosis, tumour histotype, and 16 other personal characteristics of the women.

RESULTS

During 17.7 years' average follow-up, 13,222 women were diagnosed with ovarian cancer, and 8697 of them died from the disease. Stage at diagnosis was a major determinant of survival (stage IV vs I, RR=10.54, 95% CI: 9.16-12.13). Histotype remained a significant predictor after adjustment for stage and other factors, but associations varied over the follow-up period. Histotype-specific survival was worse for high-grade than low-grade tumours. Survival appeared worse with older age at diagnosis (per 5 years: RR=1.19, 95% CI: 1.15-1.22), higher BMI (per 5-unit increase: RR=1.06, 95% CI: 1.02-1.11), and smoking (current vs never: RR=1.17, 95% CI: 1.07-1.27), but there was little association with 13 other pre-diagnostic reproductive, anthropometric, and lifestyle factors.

CONCLUSION

Stage at diagnosis is a strong predictor of ovarian cancer survival, but tumour histotype and grade remain predictors of survival even after adjustment for stage and other factors, contributing further evidence of biological dissimilarity between the ovarian cancer histotypes. Obesity and smoking represent potentially-modifiable determinants of survival, but the stronger association with stage suggests that improving earlier diagnosis would have a greater impact on increasing ovarian cancer survival.

High Prediagnosis Inflammation-Related Risk Score Associated with Decreased Ovarian Cancer Survival

BACKGROUND

There is suggestive evidence that inflammation is related to ovarian cancer survival. However, more research is needed to identify inflammation-related factors that are associated with ovarian cancer survival and to determine their combined effects.

METHODS

This analysis used pooled data on 8,147 women with invasive epithelial ovarian cancer from the Ovarian Cancer Association Consortium. The prediagnosis inflammation-related exposures of interest included alcohol use; aspirin use; other nonsteroidal anti-inflammatory drug use; body mass index; environmental tobacco smoke exposure; history of pelvic inflammatory disease, polycystic ovarian syndrome, and endometriosis; menopausal hormone therapy use; physical inactivity; smoking status; and talc use. Using Cox proportional hazards models, the relationship between each exposure and survival was assessed in 50% of the data. A weighted inflammation-related risk score (IRRS) was developed, and its association with survival was assessed using Cox proportional hazards models in the remaining 50% of the data.

RESULTS

There was a statistically significant trend of increasing risk of death per quartile of the IRRS [HR = 1.09; 95% confidence interval (CI), 1.03-1.14]. Women in the upper quartile of the IRRS had a 31% higher death rate compared with the lowest quartile (95% CI, 1.11-1.54).

CONCLUSIONS

A higher prediagnosis IRRS was associated with an increased mortality risk after an ovarian cancer diagnosis. Further investigation is warranted to evaluate whether postdiagnosis exposures are also associated with survival.

IMPACT

Given that pre- and postdiagnosis exposures are often correlated and many are modifiable, our study results can ultimately motivate the development of behavioral recommendations to enhance survival among patients with ovarian cancer.

Smoking and Neuropsychiatric Disease-Associations and Underlying Mechanisms

Despite extensive efforts to combat cigarette smoking/tobacco use, it still remains a leading cause of global morbidity and mortality, killing more than eight million people each year. While tobacco smoking is a major risk factor for non-communicable diseases related to the four main groups—cardiovascular disease, cancer, chronic lung disease, and diabetes—its impact on neuropsychiatric risk is rather elusive. The aim of this review article is to emphasize the importance of smoking as a potential risk factor for neuropsychiatric disease and to identify central pathophysiological mechanisms that may contribute to this relationship. There is strong evidence from epidemiological and experimental studies indicating that smoking may increase the risk of various neuropsychiatric diseases, such as dementia/cognitive decline, schizophrenia/psychosis, depression, anxiety disorder, and suicidal behavior induced by structural and functional alterations of the central nervous system, mainly centered on inflammatory and oxidative stress pathways. From a public health perspective, preventive measures and policies designed to counteract the global epidemic of smoking should necessarily include warnings and actions that address the risk of neuropsychiatric disease.

Identification of Hypoxia Signature to Assess the Tumor Immune Microenvironment and Predict Prognosis in Patients with Ovarian Cancer

BACKGROUND

The 5-year overall survival rate of ovarian cancer (OC) patients is less than 40%. Hypoxia promotes the proliferation of OC cells and leads to the decline of cell immunity. It is crucial to find potential predictors or risk model related to OC prognosis. This study aimed at establishing the hypoxia-associated gene signature to assess tumor immune microenvironment and predicting the prognosis of OC.

METHODS

The gene expression data of 378 OC patients and 370 OC patients were downloaded from datasets. The hypoxia risk model was constructed to reflect the immune microenvironment in OC and predict prognosis.

RESULTS

8 genes (AKAP12, ALDOC, ANGPTL4, CITED2, ISG20, PPP1R15A, PRDX5, and TGFBI) were included in the hypoxic gene signature. Patients in the high hypoxia risk group showed worse survival. Hypoxia signature significantly related to clinical features and may serve as an independent prognostic factor for OC patients. 2 types of immune cells, plasmacytoid dendritic cell and regulatory T cell, showed a significant infiltration in the tissues of the high hypoxia risk group patients. Most of the immunosuppressive genes (such as ARG1, CD160, CD244, CXCL12, DNMT1, and HAVCR1) and immune checkpoints (such as CD80, CTLA4, and CD274) were upregulated in the high hypoxia risk group. Gene sets related to the high hypoxia risk group were associated with signaling pathways of cell cycle, MAPK, mTOR, PI3K-Akt, VEGF, and AMPK.

CONCLUSION

The hypoxia risk model could serve as an independent prognostic indicator and reflect overall immune response intensity in the OC microenvironment.

A healthy lifestyle and survival among women with ovarian cancer

Ovarian cancer has a poor survival rate and, understandably, women often want to know whether there is anything they can do to improve their prognosis. Our goal was to investigate the association between a healthy lifestyle prediagnosis and postdiagnosis and survival in a cohort of Australian women with invasive epithelial ovarian cancer. We calculated a healthy lifestyle index (HLI) based on women's self-reported smoking status, height, weight, physical activity, diet and alcohol consumption before diagnosis (n = 678) and after completing primary treatment (n = 512). Clinical data and vital status for each woman were ascertained through medical records. Cox proportional hazards regression was conducted to calculate hazard ratios (HR) and 95% confidence interval (CI) for all-cause mortality. There was a suggestive association between a more healthy lifestyle before diagnosis and better survival (HR 0.79, 95% CI: 0.59-1.04), however, the association was stronger for lifestyle after diagnosis, with women in the highest tertile having significantly better survival than women in the lowest tertile (HR 0.61, 95% CI: 0.40-0.93; P-trend = .02). Current smoking, particularly postdiagnosis, was associated with higher mortality (HR 1.68, 95% CI: 1.17-2.42; HR 2.82, 95% CI: 1.29-6.14, for prediagnosis and postdiagnosis smoking, respectively), but women who quit after diagnosis had survival outcomes similar to nonsmokers (HR 0.99, 95% CI: 0.57-1.72). Higher physical activity after diagnosis was associated with better survival (HR 0.60, 95% CI: 0.39-0.92; P-trend = .02). A healthy lifestyle after diagnosis, in particular not smoking and being physically active, may help women with ovarian cancer improve their prognosis.

Prediagnosis and postdiagnosis smoking and survival following diagnosis with ovarian cancer

Little is known about the influence of prediagnosis and postdiagnosis smoking and smoking cessation on ovarian cancer survival. We investigated this relationship in two prospective cohort studies, the Nurses' Health Study (NHS) and NHSII. Analyses included 1,279 women with confirmed invasive, Stage I-III epithelial ovarian cancer. We used Cox proportional hazards regression models to estimate hazard ratios (HR) and 95% confidence intervals (CI) for ovarian cancer-specific mortality by smoking status, adjusting for age and year of diagnosis, tumor stage, histologic subtype, body mass index and nonsteroidal anti-inflammatory use (postdiagnosis models only). When examining prediagnosis smoking status (assessed a median of 12 months before diagnosis), risk of death was significantly increased for former smokers (HR = 1.19, 95% CI: 1.02-1.39), and suggestively for current smokers (HR = 1.21, 95% CI: 0.96-1.51) vs. never smokers. Longer smoking duration (≥20 years vs. never, HR = 1.23, 95% CI: 1.05-1.45) and higher pack-years (≥20 pack-years vs. never, HR = 1.28, 95% CI: 1.07-1.52) were also associated with worse outcome. With respect to postdiagnosis exposure, women who smoked ≥15 cigarettes per day after diagnosis (assessed a median of 11 months after diagnosis) had increased mortality compared to never smokers (HR = 2.34, 95% CI: 1.63-3.37). Those who continued smoking after diagnosis had 40% higher mortality (HR = 1.40, 95% CI: 1.05-1.87) compared to never smokers. Overall, our results suggest both prediagnosis and postdiagnosis smoking are associated with worse ovarian cancer outcomes.

Post-diagnosis smoking and risk of cardiovascular, cancer, and all-cause mortality in survivors of 10 adult cancers: a prospective cohort study

Several studies have examined the relationship between smoking and mortality in cancer survivors. However, few have reported the relationships in several cancer sites (i.e., bladder, non-melanoma skin, uterine, melanoma, and lymphoma), and limited data exist on the dose-response relationship between number of cigarettes smoked per day or duration of smoking cessation and mortality. Cancer survivors (N = 35,093, 61% female, mean age = 47 years old) from the National Health Interview Survey with linked data retrieved from the National Death Index served as our study participants. Cox proportional-hazards models were used to assess associations between smoking status, all-cause, and disease-specific mortality. After a median follow-up of 13 years, 11,066 deaths occurred. Survivors who reported smoking at study entry had a 73%, 75%, 85% higher risk for cardiovascular disease, cancer, and all-cause mortality, respectively when compared to nonsmokers. Former smokers had a 31% and 37% higher risk of all-cause and cancer mortality, respectively when compared to nonsmokers. The observed relationships appeared to differ by the number of cigarettes smoked (i.e., ≥ 10 per day), especially for breast, cervix, lung, prostate, uterine and non-melanoma skin cancer survivors. Those who continued smoking post diagnosis were at greatest risk of all-cause and cancer mortality, but the associations varied substantially by cancer site. These data provide sufficient evidence of the health hazards associated with smoking for cancer survivors and provide further support for public health strategies designed to curb smoking in this vulnerable population.

Joint tobacco smoking and alcohol intake exacerbates cancer risk in women- the Danish nurse cohort

PURPOSE

To explore separate and combined tobacco and alcohol use and risk of overall, smoking-related, alcohol-related, breast and gynecological cancers in women.

METHOD

Questionnaires from 19,898 women in The Danish Nurse Cohort in 1993 were linked to registries on hospitalizations, death causes and migration until Dec 2016. Cancer risk by tobacco and alcohol was estimated using Cox proportional hazards models.

RESULTS

16,106 nurses, aged >44 years (mean = 56), were eligible for analysis. Throughout 23 years (mean follow-up = 18.8 years) overall cancers counted 4,968. Of these, 1,897, 2,231, 1,407 and 579 events were smoking-related, alcohol-related, breast cancers and gynecological cancers. Increased risks of overall, smoking-related, and breast cancer were observed for current smoking and excess alcohol intake (>14 units/week), separately, compared to never smoking and light drinking (1-7 units/week) respectively. Moderate drinking (8-14 units/week) increased the risk of alcohol-related and breast cancer. Additional risk increases were observed among smokers drinking alcohol above light levels for overall, smoking-related, alcohol-related and breast cancer (HR = 1.40, 95% CI:1.30-1.51, HR = 1.72, 95% CI:1.52-1.94, HR = 1.33, 95% CI:1.26-1.40, HR = 1.32, 95% CI:1.15-1.53, respectively), compared to non-smokers drinking lightly. These risks increased further for smokers drinking above moderate levels (HR = 1.49, 95% CI:1.36-1.63, HR = 1.97, 95% CI:171.-2.26, HR = 1.40, 95% CI:1.22-1.60, HR = 1.33, 95% CI:1.12-1.57, respectively). No significant associations were found for gynecological cancer.

CONCLUSIONS

Smoking and alcohol, both separately and combined, increased risks of overall, smoking-related, alcohol-related and breast cancer; combined use resulted in incremental risk increases. Co-use of smoking and alcohol represent an extensive threat to public health; thus, prevention could benefit from combined targeting.

Association between Cigarette Smoking and Histotype-Specific Epithelial Ovarian Cancer: A Review of Epidemiologic Studies

Many studies have demonstrated that smoking can influence ovarian cancer risk and survival; however, the number of studies investigating this relationship according to histologic subtypes is limited. We conducted a review of epidemiologic research that assessed the role of smoking on ovarian cancer risk and survival after diagnosis, specifically capturing studies that discerned between various histologic subtypes of this disease. In the majority of studies, current smoking was associated with increased risk of mucinous cancer. There was also evidence of a decreased risk of clear cell and endometrioid histotypes. No significant association was observed between cigarette smoking and serous cancer. In the studies investigating the relationship between smoking and survival, all the studies reported an increased risk of mortality associated with smoking. Smoking appeared to be a risk factor for both ovarian cancer risk and mortality. Future studies need to investigate further a potential link between smoking and ovarian cancer by having a better assessment of exposure to smoking and having a larger number of participants with the ability to detect associations within rare histotypes.

Ovarian cancer risk factors by tumor aggressiveness: An analysis from the Ovarian Cancer Cohort Consortium

Ovarian cancer risk factors differ by histotype; however, within subtype, there is substantial variability in outcomes. We hypothesized that risk factor profiles may influence tumor aggressiveness, defined by time between diagnosis and death, independent of histology. Among 1.3 million women from 21 prospective cohorts, 4,584 invasive epithelial ovarian cancers were identified and classified as highly aggressive (death in <1 year, n = 864), very aggressive (death in 1 to < 3 years, n = 1,390), moderately aggressive (death in 3 to < 5 years, n = 639), and less aggressive (lived 5+ years, n = 1,691). Using competing risks Cox proportional hazards regression, we assessed heterogeneity of associations by tumor aggressiveness for all cases and among serous and endometrioid/clear cell tumors. Associations between parity (p_het = 0.01), family history of ovarian cancer (p_het = 0.02), body mass index (BMI; p_het ≤ 0.04) and smoking (p_het < 0.01) and ovarian cancer risk differed by aggressiveness. A first/single pregnancy, relative to nulliparity, was inversely associated with highly aggressive disease (HR: 0.72; 95% CI [0.58-0.88]), no association was observed for subsequent pregnancies (per pregnancy, 0.97 [0.92-1.02]). In contrast, first and subsequent pregnancies were similarly associated with less aggressive disease (0.87 for both). Family history of ovarian cancer was only associated with risk of less aggressive disease (1.94 [1.47-2.55]). High BMI (≥35 vs. 20 to < 25 kg/m² , 1.93 [1.46-2.56] and current smoking (vs. never, 1.30 [1.07-1.57]) were associated with increased risk of highly aggressive disease. Results were similar within histotypes. Ovarian cancer risk factors may be directly associated with subtypes defined by tumor aggressiveness, rather than through differential effects on histology. Studies to assess biological pathways are warranted.

Ovarian cancer risk factors by tumor aggressiveness: An analysis from the Ovarian Cancer Cohort Consortium

Ovarian cancer risk factors differ by histotype; however, within subtype, there is substantial variability in outcomes. We hypothesized that risk factor profiles may influence tumor aggressiveness, defined by time between diagnosis and death, independent of histology. Among 1.3 million women from 21 prospective cohorts, 4,584 invasive epithelial ovarian cancers were identified and classified as highly aggressive (death in <1 year, n = 864), very aggressive (death in 1 to < 3 years, n = 1,390), moderately aggressive (death in 3 to < 5 years, n = 639), and less aggressive (lived 5+ years, n = 1,691). Using competing risks Cox proportional hazards regression, we assessed heterogeneity of associations by tumor aggressiveness for all cases and among serous and endometrioid/clear cell tumors. Associations between parity (phet = 0.01), family history of ovarian cancer (phet = 0.02), body mass index (BMI; phet ≤ 0.04) and smoking (phet < 0.01) and ovarian cancer risk differed by aggressiveness. A first/single pregnancy, relative to nulliparity, was inversely associated with highly aggressive disease (HR: 0.72; 95% CI [0.58-0.88]), no association was observed for subsequent pregnancies (per pregnancy, 0.97 [0.92-1.02]). In contrast, first and subsequent pregnancies were similarly associated with less aggressive disease (0.87 for both). Family history of ovarian cancer was only associated with risk of less aggressive disease (1.94 [1.47-2.55]). High BMI (≥35 vs. 20 to < 25 kg/m2 , 1.93 [1.46-2.56] and current smoking (vs. never, 1.30 [1.07-1.57]) were associated with increased risk of highly aggressive disease. Results were similar within histotypes. Ovarian cancer risk factors may be directly associated with subtypes defined by tumor aggressiveness, rather than through differential effects on histology. Studies to assess biological pathways are warranted.

Ovarian cancer risk factors by tumor aggressiveness: An analysis from the Ovarian Cancer Cohort Consortium

Ovarian cancer risk factors differ by histotype; however, within subtype, there is substantial variability in outcomes. We hypothesized that risk factor profiles may influence tumor aggressiveness, defined by time between diagnosis and death, independent of histology. Among 1.3 million women from 21 prospective cohorts, 4,584 invasive epithelial ovarian cancers were identified and classified as highly aggressive (death in <1 year, n = 864), very aggressive (death in 1 to < 3 years, n = 1,390), moderately aggressive (death in 3 to < 5 years, n = 639), and less aggressive (lived 5+ years, n = 1,691). Using competing risks Cox proportional hazards regression, we assessed heterogeneity of associations by tumor aggressiveness for all cases and among serous and endometrioid/clear cell tumors. Associations between parity (p_het = 0.01), family history of ovarian cancer (p_het = 0.02), body mass index (BMI; p_het ≤ 0.04) and smoking (p_het < 0.01) and ovarian cancer risk differed by aggressiveness. A first/single pregnancy, relative to nulliparity, was inversely associated with highly aggressive disease (HR: 0.72; 95% CI [0.58-0.88]), no association was observed for subsequent pregnancies (per pregnancy, 0.97 [0.92-1.02]). In contrast, first and subsequent pregnancies were similarly associated with less aggressive disease (0.87 for both). Family history of ovarian cancer was only associated with risk of less aggressive disease (1.94 [1.47-2.55]). High BMI (≥35 vs. 20 to < 25 kg/m² , 1.93 [1.46-2.56] and current smoking (vs. never, 1.30 [1.07-1.57]) were associated with increased risk of highly aggressive disease. Results were similar within histotypes. Ovarian cancer risk factors may be directly associated with subtypes defined by tumor aggressiveness, rather than through differential effects on histology. Studies to assess biological pathways are warranted.

Going to extremes: determinants of extraordinary response and survival in patients with cancer

Research into factors affecting treatment response or survival in patients with cancer frequently involves cohorts that span the most common range of clinical outcomes, as such patients are most readily available for study. However, attention has turned to highly unusual patients who have exceptionally favourable or atypically poor responses to treatment and/or overall survival, with the expectation that patients at the extremes may provide insights that could ultimately improve the outcome of individuals with more typical disease trajectories. While clinicians can often recount surprising patients whose clinical journey was very unusual, given known clinical characteristics and prognostic indicators, there is a lack of consensus among researchers on how best to define exceptional patients, and little has been proposed for the optimal design of studies to identify factors that dictate unusual outcome. In this Opinion article, we review different approaches to identifying exceptional patients with cancer and possible study designs to investigate extraordinary clinical outcomes. We discuss pitfalls with finding these rare patients, including challenges associated with accrual of patients across different treatment centres and time periods. We describe recent molecular and immunological factors that have been identified as contributing to unusual patient outcome and make recommendations for future studies on these intriguing patients.

Joint exposure to smoking, excessive weight, and physical inactivity and survival of ovarian cancer patients, evidence from the Ovarian Cancer Association Consortium

PURPOSE

Previous epidemiologic studies have shown that smoking, obesity, and physical inactivity are associated with poor survival following a diagnosis of ovarian cancer. Yet, the combined relationship of these unfavorable lifestyle factors on ovarian cancer survival has not been sufficiently investigated.

METHODS

Using data pooled from 13 studies, we examined the associations between combined exposures to smoking, overweight/obesity weight, and physical inactivity and overall survival (OS) as well as progression-free survival (PFS) among women diagnosed with invasive epithelial ovarian carcinoma (n = 7,022). Using age- and stage-adjusted Cox proportional hazards regression models, we estimated hazard ratios (HRs) and 95% confidence intervals (CIs) associated with joint exposure to these factors.

RESULTS

Combined exposure to current smoking, overweight/obesity, and physical inactivity prior to diagnosis was associated with a significantly increased risk of mortality compared to women who never smoked, had normal body mass index (BMI), and were physically active (HR = 1.37; 95% CI 1.10-1.70). The association for a joint exposure to these factors exceeded that of each exposure individually. In fact, exposure to both current smoking and overweight/obesity, and current smoking and physical inactivity was also associated with increased risk of death (HR = 1.28; 95% CI 1.08-1.52, and HR = 1.26; 95% CI 1.04-1.54, respectively). The associations were of a similar magnitude when former smoking was assessed in combination with the other exposures and when excessive weight was limited to obesity only. No significant associations were observed between joint exposure to any of these factors and PFS.

CONCLUSIONS

Joint exposure to smoking, excessive weight, and physical inactivity may negatively impact survival of ovarian cancer patients. These results suggest the importance of examining the combined effect of lifestyle factors on ovarian cancer patients' survival.

Anthropometric characteristics and ovarian cancer risk and survival

PURPOSE

Multiple studies have examined the role of anthropometric characteristics in ovarian cancer risk and survival; however, their results have been conflicting. We investigated the associations between weight change, height and height change and risk and outcome of ovarian cancer using data from a large population-based case-control study.

METHODS

Data from 699 ovarian cancer cases and 1,802 controls who participated in the HOPE study were included. We used unconditional logistic regression adjusted for age, race, number of pregnancies, use of oral contraceptives, and family history of breast or ovarian cancer to examine the associations between self-reported height and weight and height change with ovarian cancer risk. Cox proportional hazards regression models adjusted for age and stage were used to examine the association between the exposure variables and overall and progression-free survival among ovarian cancer cases.

RESULTS

We observed an increased risk of ovarian cancer mortality and progression for gaining more than 20 pounds between ages 18-30, HR 1.36; 95% CI 1.05-1.76, and HR 1.31; 95% CI 1.04-1.66, respectively. Losing weight and gaining it back multiple times was inversely associated with both ovarian cancer risk, OR 0.78; 95% CI 0.63-0.97 for 1-4 times and OR 0.73; 95% CI 0.54-0.99 for 5-9 times, and mortality, HR 0.63; 95% CI 0.40-0.99 for 10-14 times. Finally, being taller during adolescence and adulthood was associated with increased risk of mortality. Taller stature and weight gain over lifetime were not related to ovarian cancer risk.

CONCLUSIONS

Our results suggest that height and weight and their change over time may influence ovarian cancer risk and survival. These findings suggest that biological mechanisms underlying these associations may be hormone driven and may play an important role in relation to ovarian carcinogenesis and tumor progression.

Current Gaps in Ovarian Cancer Epidemiology: The Need for New Population-Based Research

With recent ovarian cancer screening studies showing no clinically significant mortality benefit, preventing this disease, identifying high-risk populations, and extending survival remain priorities. However, several challenges are impeding progress in ovarian cancer research. With most studies capturing exposure information from 10 or more years ago, evaluation of how changing patterns of exposures, such as new oral contraceptive formulations and increased intrauterine device use, might influence ovarian cancer risk and survival is difficult. Risk factors for ovarian cancer should be evaluated in the context of tumor histotypes, which have unique molecular features and cells of origin; this is a task that requires large collaborative studies to achieve meaningful sample sizes. Importantly, identification of novel modifiable risk factors, in addition to those currently known to reduce risk (eg, childbearing, tubal ligation, oral contraceptive use), is needed; this is not feasibly implemented at a population level. In this Commentary, we describe important gaps in knowledge and propose new approaches to advance epidemiologic research to improve ovarian cancer prevention and survival, including updated classification of tumors, collection of data on changing and novel exposures, longer follow-up on existing studies, evaluation of diverse populations, development of better risk prediction models, and collaborating prospectively with consortia to develop protocols for new studies that will allow seamless integration for future pooled analyses.