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Abstract P4-07-03: The impact of HIV on non-adherence for tamoxifen among women with breast cancer in South Africa

2023· article· en· W4322775162 on OpenAlexaff
Oluwatosin A Ayeni, Shingirai Chiwambutsa, Wenlong Carl Chen, Nyasha Kapungu, Comfort Kanji, Roslyn Thelingwani, Nivashni Murugan, Rophiwa Mathiba, Boitumelo Phakathi, Sarah Nietz, Duvern Ramiah, Daniel S. O’Neil, Judith S. Jacobson, Paul Ruff, Herbert Cubasch, Tobias Chirwa, Maureen Joffe, Collen Masimirembwa, Alfred I. Neugut

Bibliographic record

VenueCancer Research · 2023
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS drug development and treatment
Canadian institutionsColumbia College
Fundersnot available
KeywordsTamoxifenMedicineBreast cancerInterquartile rangeInternal medicineOncologyProspective cohort studyCohortCancerLogistic regressionGynecology

Abstract

fetched live from OpenAlex

Abstract Introduction HIV-positive women with breast cancer (BC) have worse overall survival than HIV-negative women with BC, and poor adherence to prescribed tamoxifen is known to contribute to poor survival. We, therefore, investigated the association of HIV infection with adherence to adjuvant tamoxifen among women with localized hormone receptor (HR)-positive breast cancer in South Africa. Methods Among 4,097 women diagnosed with breast cancer at six hospitals in the prospective South African Breast Cancer and HIV Outcomes (SABCHO) cohort study between July 2015 and December 2020, we focused on women with stages I-III HR-positive breast cancer who were prescribed 20mg of adjuvant tamoxifen daily for ≥3 months during the study period. We collected venous blood once from each participant during a routine clinic visit and analyzed concentrations of tamoxifen and its metabolites using a triple quadruple mass spectrometer. We defined non-adherence as a tamoxifen level < 60ng/mL after 3 months of prescribed daily tamoxifen use. We compared socio-demographic, lifestyle factors, tamoxifen-related side effects, and concurrent medication use among women with and without HIV and developed multivariable logistic regression models of tamoxifen non-adherence. Results Among 369 participants, 78 (21.1%) were HIV-positive and 291 (78.9%) HIV-negative. After a median (interquartile range) time of 13.0 (6.2-25.2) months since tamoxifen initiation, the tamoxifen serum concentration ranged between 1.54 and 943.0ng/mL, with a median of 52.3ng/mL. In the full cohort, 208 women (56.4%) were non-adherent to tamoxifen; only 161 (43.6%) were adherent. Women < 40 years of age were less likely to adhere to tamoxifen than women >60 years (73.4% vs 52.6%, odds ratio (OR)=2.49, 95% confidence interval (CI)=1.26-4.94); likewise, HIV-positive women (70.5% vs 52.6%, OR=2.16, 95% CI=1.26-3.70) were less likely to adhere than HIV-negative women. In an adjusted model, only HIV was associated with non-adherence; HIV-positive women had twice the odds of non-adherence to tamoxifen, compared to HIV-negative women (OR=2.40, 95% CI=1.11-5.20). Conclusion Non-adherence to tamoxifen may limit the overall survival of women with HR-positive breast cancer; in our study, especially in HIV-positive women. Citation Format: Oluwatosin A Ayeni, Shingirai Chiwambutsa, Wenlong Carl Chen, Nyasha N. Kapungu, Comfort Kanji, Roslyn Thelingwani, Nivashni Murugan, Rophiwa Mathiba, Boitumelo Phakathi, Sarah Nietz, Duvern Ramiah, Daniel S. O’Neil, Judith S. Jacobson, Paul Ruff, Herbert Cubasch, Tobias Chirwa, Maureen Joffe, Collen Masimirembwa, Alfred I. Neugut. The impact of HIV on non-adherence for tamoxifen among women with breast cancer in South Africa [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P4-07-03.

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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)0.001
metaresearch head score (Gemma)0.004
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 score0.037
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.068
GPT teacher head0.398
Teacher spread0.329 · 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
Published2023
Admission routes1
Has abstractyes

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