Prognostic factors of adjuvant chemotherapy discontinuation among stage III colon cancer patients: A survey of medical oncologists and a systematic review and meta‐analysis
Bibliographic record
Abstract
Abstract Background Factors that are prognostic of early discontinuation of adjuvant chemotherapy among stage III colon cancer patients have yet to be described. To address this gap, a survey of medical oncologists and a systematic review and meta‐analysis were conducted. Methods A survey was distributed in March 2019 to medical oncologists who treat colon cancer within Alberta, Canada. Clinicians were asked to rank the prognostic importance of a set of variables using a Likert scale and agreement was quantified using a weighted Cohen's kappa. In addition, we systematically searched four databases up to July 2019. Meta‐analyses were conducted using a random‐effects model. Results Of the 25 clinicians who were sent the survey, 14 responded. Overall, there was no agreement regarding which variables were prognostic of early discontinuation (weighted Cohen's kappa = 0.12; 95% CI = 0.05‐0.18). From an initial 3927 articles, 18 investigations were identified for inclusion in our review. Based upon evidence from both the survey and the systematic review, the following four variables were identified as being prognostic of early discontinuation: (a) comorbidity (OR2+ vs 0 = 1.53; 95% CI = 1.30‐1.79); (b) performance status (ORECOG 2+ vs 0‐1 = 1.33; 95%CI = 1.07‐1.65); (c) T stage (ORT4 vs T1‐2 = 1.57; 95% CI = 0.99‐2.50); and (d) chemotherapy regimen (estimates not pooled due to heterogeneity). In addition to these factors, there was some suggestion that age, marital status/social support, muscle mass, N stage, and tumor grade had prognostic value. Conclusions Current evidence is heterogeneous and limited. Additional research is needed to confirm our findings and to explore additional prognostic 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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.019 | 0.060 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.018 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".