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Physician-reported reasons for non-enrollment of older adults in cancer clinical trials.

2018· article· en· W4241615461 on OpenAlexaff
Miki J. Lackman, Tina Hsu

Bibliographic record

VenueJournal of Clinical Oncology · 2018
Typearticle
Languageen
FieldMedicine
TopicAdvances in Oncology and Radiotherapy
Canadian institutionsOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsMedicineLogistic regressionCancerWilcoxon signed-rank testContinuous variableInternal medicineMedical diagnosisExact testSystemic therapyComorbidityDiseaseMann–Whitney U testBreast cancerPathology

Abstract

fetched live from OpenAlex

e18608 Background: Older adults (OA), age 65+, account for 60% of new cancer diagnoses but only 22-36% of those in clinical trials (CT). Prior studies surveyed physicians to recall reasons for not enrolling OA in general rather than assessing reasons for specific patients seen. Objectives: 1) Identify the percentage of OA vs younger adults (YA) offered CT enrollment; 2) Identify physician-reported reasons for non-enrollment of OA vs YA to CT Methods: Consecutive cancer patients (n = 503) seen in consultation at a single centre were enrolled. Patient, cancer characteristics and information about systemic therapy (type, whether accepted, and if CT was offered) were recorded from the consult note. For patients who accepted systemic therapy, but were not offered CT, medical oncologists were contacted to determine reason for not offering CT. Results were summarized using descriptive statistics. Comparison of YA and OA was done using the Chi-square or Fisher exact test for categorical variables and Wilcoxon rank sum test for continuous variables. Logistic regression was used to determine the association between age and the likelihood of being offered CT. Results: Median patient age was 66. Breast (31.2%) and gastrointestinal (25.6%) cancers were most common. Almost 40% had incurable disease. OA had more comorbidities (Charlson Comorbidity Index 2+ 24.7 vs 10%), took more medications (mean 4.2 vs 2.3), and had worse performance status (PS) (ECOG 3+ 15.1 vs 5.2%) than YA (p < 0.0001). OA were less likely to be offered systemic therapy (68.3 vs 82.1%, p < 0.001) but were as likely to accept as YA. OA were less likely to be offered a CT (14.8 vs 32.1%, p < 0.001). No available CT (75.4%), poor PS (7.8%) and ineligiblity for available CT (6.3%) were the most commonly cited reasons for not offering CT to OA and YA. Poor PS in OA was more commonly cited as a reason for not offering CT compared to YA (11.8 vs 3.9%). After adjusting for patient factors including PS and comorbidities, increasing age (by decade) was associated with a lower likelihood of being offered CT OR 0.74 (95% CI 0.6-0.9, p < 0.001). Conclusions: OA are less likely to be offered but as likely to accept systemic therapy as YA. OA are less likely to be offered CT as YA even after accounting for patient factors.

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)0.008
metaresearch head score (Gemma)0.038
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 score0.008
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.038
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.223
GPT teacher head0.631
Teacher spread0.408 · 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
Published2018
Admission routes1
Has abstractyes

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