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PD34-01 EVALUATION OF FERTILITY PRESERVATION PRACTICES AMONG ONCOLOGISTS: REVIEW OF ASCO’S QUALITY ONCOLOGY PRACTICE INITIATIVE STANDARDS FOR CANCER CARE

2019· article· en· W2942091366 on OpenAlexaboutno aff
Premal Patel, Benjamin Shiff, Taylor P. Kohn, Ridwan Alam, Ranjith Ramasamy

Bibliographic record

VenueThe Journal of Urology · 2019
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Financial Impacts of Cancer
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineFertility preservationFamily medicineCancerGynecologyOncologyFertilityInternal medicineEnvironmental healthPopulation

Abstract

fetched live from OpenAlex

You have accessJournal of UrologyInfertility: Therapy I (PD34)1 Apr 2019PD34-01 EVALUATION OF FERTILITY PRESERVATION PRACTICES AMONG ONCOLOGISTS: REVIEW OF ASCO’S QUALITY ONCOLOGY PRACTICE INITIATIVE STANDARDS FOR CANCER CARE Premal Patel*, Benjamin Shiff, Taylor Kohn, Ridwan Alam, and Ranjith Ramasamy Premal Patel*Premal Patel* More articles by this author , Benjamin ShiffBenjamin Shiff More articles by this author , Taylor KohnTaylor Kohn More articles by this author , Ridwan AlamRidwan Alam More articles by this author , and Ranjith RamasamyRanjith Ramasamy More articles by this author View All Author Informationhttps://doi.org/10.1097/01.JU.0000556284.03529.1cAboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVES: The ASCO Quality Oncology Practice Initiative is an oncologist-led practice-based quality assessment program to promote excellence in cancer care. A total of 994 practices submit data on over 32,000 patients. We utilized their dataset to identify the proportion and predictors of discussing fertility risks and fertility preservation prior to initiating cancer therapy among patients of reproductive age. METHODS: Reproductive age was defined as 18-40 and 18-50 for females and males, respectively. We assessed whether fertility risks and fertility preservation options were discussed prior to chemotherapy with patients of reproductive age. We also assessed whether a referral to a specialist was made. Multivariable linear regression was performed to identify predictors of fertility preservation counselling controlling for practice type (academic vs. private), geographic location (region and state) and state legislature mandating insurance coverage for fertility preservation. RESULTS: A total of 136,746 charts were reviewed with a total of 27,052 patients identified as being of reproductive age. Overall, 41.8% of patient of reproductive age had a discussion regarding the risk of infertility associated with chemotherapy while 27.7% of patients had fertility preservation options discussed or were referred to a specialist. On multivariable linear regression being seen at an academic institution was associated with more frequent discussion of fertility risk (48.0% vs 40.4%, p = 0.04) and more frequent discussion of fertility preservation options (34.0% vs 25.5%, p = 0.004) when compared with private practices. States in which laws mandate coverage of fertility preservation were associated with significantly higher rates of discussion (48.6% vs 39.6%, p = 0.0003) and more frequent discussion of fertility preservation (32.9% vs 25.1%, p = 0.0003). There has been no increase in either discussion of risk or fertility preservation from 2015 to 2018. State and region were not significantly associated with differences in discussions. CONCLUSIONS: Despite institution of guidelines mandating fertility preservation, less than half of providers appear to discuss risks and options. Providers in academic institutions and providers in states that mandate fertility preservation appear to discuss options more frequently as compared to providers in private practices and states that lack coverage. Further research is necessary to increase fertility preservation awareness aimed at both patients and providers. Source of Funding: Department of Urology, University of Miami Miami, FL; Winnipeg, Canada; Baltimore, MD; Miami, FL© 2019 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 201Issue Supplement 4April 2019Page: e644-e645 Advertisement Copyright & Permissions© 2019 by American Urological Association Education and Research, Inc.MetricsAuthor Information Premal Patel* More articles by this author Benjamin Shiff More articles by this author Taylor Kohn More articles by this author Ridwan Alam More articles by this author Ranjith Ramasamy More articles by this author Expand All Advertisement PDF downloadLoading ...

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)0.081
metaresearch head score (Gemma)0.248
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.919
Threshold uncertainty score0.428

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0810.248
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.004
Bibliometrics0.0100.015
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0040.005
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0070.001

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 head0.187
GPT teacher head0.454
Teacher spread0.267 · 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.

Study designObservational
DomainEvaluation
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
Published2019
Admission routes1
Has abstractyes

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