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Adjuvant chemotherapy outcomes among patients with stage II early-onset colon cancer in Alberta.

2025· article· en· W4410819406 on OpenAlexaffabout
Robert B. Basmadjian, Dylan E. O’Sullivan, Tamer N. Jarada, Winson Y. Cheung, Patricia A. Tang, Sharlene Gill, Safiya Karim, Robert J. Hilsden, Colleen Cuthbert, Khara M. Sauro, Joon Lee, Christie Farrer, Barry Stein, Darren R. Brenner

Bibliographic record

VenueJournal of Clinical Oncology · 2025
Typearticle
Languageen
FieldMedicine
TopicColorectal Cancer Treatments and Studies
Canadian institutionsAlberta Health ServicesUniversity of Calgary
Fundersnot available
KeywordsMedicineStage (stratigraphy)ChemotherapyOncologyColorectal cancerAdjuvantAdjuvant chemotherapyInternal medicineCancerBreast cancer

Abstract

fetched live from OpenAlex

e15629 Background: Incidence rates of early-onset colorectal cancer (eoCRC) among adults under the age of 50 years are increasing in Canada and the United States. Despite increasing incidence, eoCRCs represent a minority of CRC diagnoses (~10%) and are underrepresented in randomized trials of novel chemotherapies and targeted agents. As such, robust evidence that can be used to inform the clinical management of eoCRC is lacking. In particular, the appropriateness of adjuvant chemotherapy for individuals with stage II colon cancer is controversial. Given this uncertainty, there is an urgent need for data to clarify whether these practices are helpful or harmful. Objective: This project leveraged existing real-world data to investigate treatment outcomes among eoCRC patients in Alberta and identify areas amenable to intervention. The specific aim was to assess the real-world effectiveness of initiating adjuvant chemotherapy vs. observation on survival in eoCRC. Methods: We conducted a population-based, retrospective cohort study including all patients aged 18to 49 years in Alberta diagnosed with invasive colon cancer from 2004 to 2020. Data from electronic medical records, administrative data claims, and vital statistics were linked. Observational data were used to emulate a target trial comparing the initiation of any adjuvant chemotherapy (fluorouracil/capecitabine-based regimens) vs. observation (no chemotherapy) within 12 weeks of diagnosis. The outcomes were recurrence-free and overall survival. Follow-up began at time of surgery and patients were followed until recurrence, death, last known date of contact with the healthcare system, or administrative end of follow-up (April 2022), whichever occurred first. To address time-varying selection bias, marginal Cox models with artificial cloning and inverse-probability censoring weights were employed to estimate hazard ratios (HR) and 95% confidence intervals (95%CI). Results: A total of 230 patients were included, where 94 (41%) initiated chemotherapy and 136 (59%) did not. Patients initiating chemotherapy were more likely to have T4 tumours (42.6% vs. 8.1%), high grade tumours (20.3% vs. 11%) and fewer than 12 examined lymph nodes (8.5% vs. 2.9%). The median time-to-chemotherapy initiation since surgery was 55 days [IQR:38-72]. The risks of recurrence and death were 21% (HR:0.79; 95%CI:0.41-1.51) and 20% (HR:0.80; 95%CI:0.40-1.61) lower among those who initiated chemotherapy versus observation, respectively, but statistical significance was not achieved. Conclusions: Our study did not demonstrate significant survival benefits of initiating adjuvant chemotherapy in stage II early-onset colon cancer. However, we were limited in sample size, outcome events, and data on microsatellite instability. Future studies should explore prediction of high-risk status to identify patients more likely to benefit from adjuvant chemotherapy.

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)0.001
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 score0.103
Threshold uncertainty score0.207

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
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 head0.038
GPT teacher head0.441
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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Citations0
Published2025
Admission routes2
Has abstractyes

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