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Adjuvant oxaliplatin and fall-related injury in patients with colorectal cancer.

2022· article· en· W4205376135 on OpenAlexafffundabout
Colin Sue‐Chue‐Lam, Christine B. Brezden, Rinku Sutradhar, Amy YX Yu, Nancy N. Baxter

Bibliographic record

VenueJournal of Clinical Oncology · 2022
Typearticle
Languageen
FieldMedicine
TopicCancer Treatment and Pharmacology
Canadian institutionsHealth Sciences CentreInstitute of Health Services and Policy ResearchSunnybrook Health Science CentreMount Sinai HospitalUniversity of Toronto
FundersPhysicians' Services Incorporated Foundation
KeywordsMedicineOxaliplatinColorectal cancerCohortHazard ratioInternal medicineProportional hazards modelPopulationRetrospective cohort studyAdjuvant chemotherapyOncologyCancerSurgeryConfidence interval

Abstract

fetched live from OpenAlex

78 Background: Adjuvant oxaliplatin improves colorectal cancer (CRC) survival but causes dose-dependent peripheral neuropathy, possibly increasing the risk of fall-related injuries (FRI) such as fractures. In this retrospective cohort study, we examined the impact of adjuvant oxaliplatin cycles on FRIs. Methods: All data were ascertained from linked health administrative and population databases. We included Ontarians aged 18-85 years at CRC diagnosis between January 1 2007 to December 31 2018 who underwent curative resection and received adjuvant oxaliplatin. We excluded those with a prior cancer diagnosis within 5 years, prior CRC diagnosis ever, non-adenocarcinoma histology, prior oxaliplatin, and <2 years of Ontario health insurance prior to CRC diagnosis. Oxaliplatin dose was determined in the 382 days after resection and dichotomized (1-6 vs. 7-12 cycles). The outcome was FRI, defined by ICD10 codes W00-W19 for any injury caused by a fall requiring emergency or inpatient care. Follow-up began at the end of the treatment window and terminated at the first of FRI, death, loss of Ontario health insurance, or March 31 2020. To account for differences between groups, clinical and demographic characteristics at diagnosis (Table) were used to estimate propensity scores for treatment and calculate inverse probability of treatment weights. These weights were applied to a Fine & Gray regression model to determine the subdistribution hazard ratio (sHR) estimating the association between FRI and 1-6 versus 7-12 cycles of oxaliplatin, with death as a competing risk. Standardized differences <0.1 indicated negligible imbalance. An interaction term tested for effect modification by age at diagnosis. Results: 9,324 patients were included in the study; 1,870 received 1-6 cycles and 7,454 received 7-12 cycles of oxaliplatin. Those exposed to 1-6 cycles were older (61.0 vs. 59.1 years), had higher comorbidity scores (13.5 vs 12.3), and more often had rectal cancer (27.5 vs. 22.2%). Negligible imbalance remained after weighting. Median follow-up was 50.2 months. Total follow-up was 44,472 person-years. There were 1,223 FRIs and 1,913 deaths. The sHR for FRIs comparing 7-12 cycles against 1-6 cycles of oxaliplatin was 0.98 (95% CI 0.85-1.14). The interaction p-value for age and oxaliplatin dose was 0.24. Conclusions: In this population-based retrospective cohort study of 9,324 patients with CRC, the risk of FRIs was similar for 7-12 cycles compared with 1-6 cycles of adjuvant oxaliplatin. This finding was consistent across age at diagnosis. Future research should examine the relationship between oxaliplatin dose and falls not resulting in injury. [Table: see text]

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)0.000
metaresearch head score (Gemma)0.001
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 score0.026
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0000.000
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 head0.047
GPT teacher head0.449
Teacher spread0.402 · 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
Published2022
Admission routes3
Has abstractyes

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