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Record W2243255469 · doi:10.1158/1538-7445.am2015-854

Abstract 854: Ovarian cancer risk factors by histologic subtypes: evidence for etiologic heterogeneity

2015· article· en· W2243255469 on OpenAlexaff
Nicolas Wentzensen, Elizabeth M. Poole, Alan A. Arslan, Alpa V. Patel, Veronica Wendy Setiawan, Kala Visvanathan, Elisabete Weiderpass, Emily White, Hans‐Olov Adami, Louise A. Brinton, Leslie Bernstein, Julie E. Buring, Lesley M. Butler, Saioa Chamosa, Tess V. Clendenen, Laure Dossus, Renée T. Fortner, Susan M. Gapstur, Mia M. Gaudet, Inger Torhild Gram, Patricia Hartge, Judith Hoffman–Bolton, Annika Idahl, Michael E. Jones, Rudolf Kaaks, Vivki Kirsh, Woon‐Puay Koh, James V. Lacey, I‐Min Lee, Eva Lundin, Melissa A. Merritt, Ulrike Peters, Jenny N. Poynter, Sabina Rinaldi, Kim Robien, Thomas E. Rohan, Dale P. Sandler, Leo J. Schouten, Louise K. Sjöholm, Sabina Sieri, Anthony J. Swerdlow, Anne Tjønneland, Britton Trabert, Lynne R. Wilkens, Alicja Wolk, Hannah Yang, Anne Zeleniuch‐Jacquotte, Shelley S. Tworoger

Bibliographic record

VenueCancer Research · 2015
Typearticle
Languageen
FieldMedicine
TopicOvarian cancer diagnosis and treatment
Canadian institutionsCancer Care OntarioUniversity of Toronto
Fundersnot available
KeywordsSerous fluidMedicineOvarian cancerClear cellOncologyEndometrial cancerCancerInternal medicineCohortRisk factorGynecologySerous carcinomaClear cell carcinomaCarcinoma

Abstract

fetched live from OpenAlex

Abstract Background: A subset of high grade serous carcinomas may arise from the fallopian tube, while some endometrioid and clear cell carcinomas may derive from endometrial tissue. Previous studies have suggested differences in ovarian cancer risk factors by histologic subtypes, but had limited sample sizes. In the Ovarian Cancer Cohort Consortium (OC3), we evaluated associations of reproductive, hormonal, demographic and lifestyle factors, and family history of cancer with ovarian cancer subtypes. Identification of potential differences in associations among subtypes is important for clarifying ovarian cancer etiology and for developing novel prevention and risk prediction approaches. Methods: Among over 1.2 million women from 21 cohort studies, 4,347 ovarian cancers with histology information were identified during follow-up (3223 serous, 555 endometrioid, 316 mucinous, 253 clear cell). We used competing risks Cox proportional hazards regression to compute risk factor associations by histologic subtype. Models were stratified on study and year of birth and adjusted for age, parity and oral contraceptive use; subtype heterogeneity was evaluated by a likelihood ratio test. Unsupervised hierarchical clustering was used to evaluate patterns of risk factors by histology. Results: Most risk factors showed significant heterogeneity across histologic subtypes. Higher parity was most strongly associated with lower risks of endometrioid (RR per child: 0.79; 95%CI: 0.74-0.85) and clear cell (RR: 0.69; 95%CI: 0.61-0.78) carcinomas (p-het<0.0001). Age at menopause was positively and tubal ligation was inversely associated only with endometrioid and clear cell carcinomas (p-het = 0.02 and 0.003, respectively). Long-term menopausal hormone use (>5 years) was associated with endometrioid carcinomas (RR: 2.23; 95% CI: 1.46-3.42) and serous carcinomas (RR: 1.66; 95% CI: 1.44-1.92), and inversely associated with clear cell carcinomas (RR: 0.43; 95% CI: 0.20-0.91; p-het = 0.001). Family history of breast cancer was associated with increased risk of serous carcinomas (RR:1.13; 95% CI:1.02-1.27) and endometrioid carcinomas (RR: 1.44; 95% CI: 1.12-1.87; p-het = 0.02). Smoking (per 20 pack years) showed a positive association with mucinous carcinomas (RR: 1.38; 95% CI: 1.09-1.75) and an inverse association with clear cell carcinomas (RR:0.62; 95% CI: 0.46-0.85; p-het = 0.001). In unsupervised hierarchical clustering, serous and mucinous carcinomas clustered in one group and endometrioid and clear cell carcinomas in the other. Conclusion: Our results demonstrate heterogeneous associations of risk factors with ovarian cancer subtypes, supporting the hypothesis that the subtypes develop through different pathways. Most established risk factors were more strongly associated with non-serous carcinomas, suggesting that risk prediction may be more challenging for serous cancers, the most fatal subtype. Citation Format: Nicolas A. Wentzensen, Elizabeth Poole, Alan A. Arslan, Alpa V. Patel, V Wendy Setiawan, Kala Visvanathan, Elisabete Weiderpass, Emily White, Hans-Olov Adami, Louise A. Brinton, Leslie Bernstein, Julie Buring, Lesley M. Butler, Saioa Chamosa, Tess V. Clendenen, Laure Dossus, Renee Fortner, Susan M. Gapstur, Mia M. Gaudet, Inger Torhild Gram, Patricia Hartge, Judith Hoffman-Bolton, Annika Idahl, Michael Jones, Rudolf Kaaks, Vivki Kirsh, Woon-Puay Koh, James V. Lacey, I-Min Lee, Eva Lundin, Melissa Merritt, Ulrike Peters, Jenny Poynter, Sabina Rinaldi, Kim Robien, Thomas Rohan, Dale P. Sandler, Leo J. Schouten, Louise Sjöholm, Sabina Sieri, Anthony Swerdlow, Anne Tjønneland, Britton Trabert, Lynne Wilkens, Alicja Wolk, Hannah P. Yang, Anne Zeleniuch-Jacquotte, Shelley S. Tworoger. Ovarian cancer risk factors by histologic subtypes: evidence for etiologic heterogeneity. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 854. doi:10.1158/1538-7445.AM2015-854

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.392
GPT teacher head0.496
Teacher spread0.104 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2015
Admission routes1
Has abstractyes

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