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Record W4282975240 · doi:10.1158/1538-7445.am2022-2248

Abstract 2248: Environmental factors associated with residual disease after ovarian cancer primary cytoreduction surgery

2022· article· en· W4282975240 on OpenAlexaff
Minh Tung Phung, Andrew Berchuck, Ellen L. Goode, Marc T. Goodman, Gillian E. Hanley, Jean L. Richardson, Bronwyn Grout, Anne Chase, Cindy McKinnon Deurloo, Beth Y. Karlan, Toon Van Gorp, Keitaro Matsuo, Karen McLean, Malcolm C. Pike, Joellen M. Schildkraut, Kathryn L. Terry, Anna DeFazio, Penelope M. Webb, Paul D.P. Pharoah, Susan J. Ramus, Celeste Leigh Pearce

Bibliographic record

VenueCancer Research · 2022
Typearticle
Languageen
FieldMedicine
TopicOvarian cancer diagnosis and treatment
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicineOvarian cancerDebulkingTubal ligationOncologyBody mass indexGynecologyFallopian tube cancerFallopian tubeOdds ratioBreast cancerInternal medicineCancerPopulationFamily planning

Abstract

fetched live from OpenAlex

Abstract Background: Ovarian cancer is the deadliest gynecologic cancer. Standard treatments for advanced stage high-grade serous ovarian cancer, the most common type, include (1) primary cytoreductive surgery (PCS) followed by adjuvant chemotherapy or (2) neoadjuvant chemotherapy (NACT) with interval debulking surgery. Patients in whom PCS is unlikely to yield optimal cytoreduction to no visible residual disease (R0) or who have medical contraindications to PCS are recommended to undergo NACT. Previous studies on associations between environmental factors and risk of any macroscopic residual disease have yielded inconsistent results. We aimed to (1) comprehensively examine the associations between demographic, lifestyle and reproductive factors and risk of residual disease after PCS; and (2) develop and internally validate a risk prediction model based on these factors. Methods: We used pooled data on 3,492 women who had PCS following a diagnosis with advanced stage high-grade serous ovarian, fallopian tube or primary peritoneal cancers from the Ovarian Cancer Association Consortium. Fifteen exposures of interest included age at diagnosis, menopausal status, race/ethnicity, education level, first-degree family history of ovarian cancer, endometriosis, smoking, body mass index, parity, incomplete pregnancy, tubal ligation, use of combined oral contraceptives, depot-medroxyprogesterone acetate, estrogen (ET), and combined estrogen-progestin therapy. We fit logistic regression models to examine each exposure-residual disease association in 80% of the data (n=2,794; random selection of participants). We developed a risk prediction model including the factors with p-values ≤0.2. Area under the receiver operating characteristic curve (AUC) was used to assess the model’s discrimination in the remaining 20% of the data (n=698). Results: Of the 3,492 participants, 2,003 (57%) had residual disease following PCS. Older age at diagnosis was associated with an increased risk of residual disease (OR=1.07 per five years, 95% CI 1.03-1.11). In contrast, a family history of ovarian cancer (OR=0.63, 95% CI 0.42-0.95) or ET use for 5+ years (OR=0.61, 95% CI 0.39-0.96) were associated with achieving R0. These above factors were included in the risk prediction model as were race/ethnicity, personal history of endometriosis, and smoking, whose p-values ≤0.2. The model showed modest performance in the validation set (AUC=0.64). Conclusions: Younger age at diagnosis, family history of ovarian cancer, and long-term ET use were associated with achieving R0 following PCS. Future studies incorporating genetic and clinical factors to improve the risk prediction for residual disease following PCS are warranted. Citation Format: Minh Tung Phung, Andrew Berchuck, Ellen L. Goode, Marc T. Goodman, Gillian E. Hanley, Jean Richardson, Bronwyn Grout, Anne Chase, Cindy McKinnon Deurloo, Beth Y. Karlan, Toon Van Gorp, Keitaro Matsuo, Karen McLean, Malcolm C. Pike, Joellen M. Schildkraut, Kathryn L. Terry, Anna DeFazio, Penelope M. Webb, Paul D. P. Pharoah, Susan J. Ramus, Celeste Leigh Pearce. Environmental factors associated with residual disease after ovarian cancer primary cytoreduction surgery [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2248.

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)0.002
metaresearch head score (Gemma)0.006
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 score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.077
GPT teacher head0.340
Teacher spread0.264 · 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
Published2022
Admission routes1
Has abstractyes

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