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Impact of treatment and frailty on elder-relevant physical function outcomes in older adults with metastatic castration-resistant prostate cancer (mCRPC).

2021· article· en· W3133841503 on OpenAlexafffund
Helen Yang, Henriette Breunis, Narhari Timilshina, Seung Yeon Kim, Shabbir M.H. Alibhai

Bibliographic record

VenueJournal of Clinical Oncology · 2021
Typearticle
Languageen
FieldMedicine
TopicFrailty in Older Adults
Canadian institutionsUniversity Health NetworkUniversity of Toronto
FundersProstate Cancer Canada
KeywordsMedicineProstate cancerEnzalutamideGrip strengthGeriatric oncologyLogistic regressionActivities of daily livingCohortProspective cohort studyPerformance statusGerontologyPhysical therapyCancerInternal medicine

Abstract

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76 Background: Maintenance of physical function is a key consideration in treatment decision-making for older adults with metastatic cancer, many of whom are frail. However, physical function outcomes with treatment, and effects of frailty, have not been adequately explored in the mCRPC setting. We evaluated the effects of frailty status and treatment with docetaxel (CHEMO), abiraterone (ABI), enzalutamide (ENZA), and radium 223 (RAD) on elder-relevant physical function outcomes in older men with mCRPC. Methods: Men aged 65+ were enrolled in this multicenter prospective observational cohort study. Daily function was evaluated with the OARS instrumental activities of daily living (IADL). Objective physical function was assessed by grip strength and the Short Physical Performance Battery (SPPB). Falls were documented during interviews. We also collected FACT-G physical well-being (PWB) and functional well-being (FWB) subscales. Assessments were performed at baseline, 3 months, and 6 months. We identified frailty status with a validated frailty index. Mixed effects regression models were used to examine the difference in primary outcomes over time by treatment group or frailty status adjusted for baseline characteristics. Factors associated with falls within 6 months of treatment initiation were determined with logistic regression. Results: A total of 70, 38, 67, and 23 men starting CHEMO, ABI, ENZA, and RAD were included. Mean age, education, race, number of medications, and BMI were similar at baseline between treatment groups. In treatment-stratified analyses without considering frailty, no significant changes over time were reported for any physical function outcome. Frailty was significantly associated with lower IADL function (p < 0.0001), worse grip strength (p < 0.0001), worse SPPB score (p < 0.0001), worse PWB (p < 0.0001), and worse FWB (p < 0.0001) at baseline. In frailty-stratified analyses, grip strength (p = 0.0345) worsened, but SPPB (p = 0.0147) improved significantly over time. Also, changes in SPPB (p = 0.0394) and PWB scores (p = 0.0269) over time differed by frailty status, where frail cohorts had greater improvement over time in both scores. Frailty and treatment type were not predictors of falls whereas prior falls history (OR: 3.52, 95% CI: 1.40-8.86) and age (OR: 1.07, 95% CI: 1.01-1.14) were significant predictors. Conclusions: Frail older men receiving treatment for mCRPC have worse IADL function, grip strength, SPPB scores, PWB, and FWB at baseline. Although grip strength worsened over time, they had greater improvement in SPPB scores and PWB over time than fit patients. Contrary to our hypothesis, most older adults do not experience significant worsening in elder-relevant physical function outcomes over time regardless of treatment. The impact of frailty requires further study.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.083
GPT teacher head0.462
Teacher spread0.379 · 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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Citations1
Published2021
Admission routes2
Has abstractyes

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