Predictors of early mortality in colorectal cancer patients undergoing chemotherapy: Results from a global prospective cohort study.
Bibliographic record
Abstract
532 Background: Early mortality is a major problem in colorectal cancer and our understanding of risk factors and predictors is incomplete. A venous thromboembolism (VTE) Risk Score, comprising primary site, baseline hemoglobin, leukocyte and platelet counts, and body mass index [Khorana et al, Blood, 2008], has been shown to be associated with early mortality in solid tumors [Kuderer et al, 2008; Ay et al, 2013]. We evaluated the value of this Risk Score and other key prognostic variables in predicting early mortality for colorectal cancer (CRC) patients. Methods: CANTARISK was a prospective, non-interventional, global cohort study in patients with CRC and lung cancer initiating a new chemotherapy regimen. Clinical data were collected at 0, 2, 4, and 6 months. All data were compiled centrally and analyzed after the study closed. Risk score categories were as defined previously [Blood, 2008]. Statistically significant univariable associations and a priori prognostic variables were tested in multivariable models; adjusted odds ratios (OR) are presented. Results: A total of 1,789 CRC patients were enrolled from 2011-12; data on 1,533 evaluable patients are presented. Median age was 62 years; 71% were Caucasian. Geographic distribution was Europe 37%, North America 28%; Asia 23%; South America 12%. One-third (33%) had a rectal primary and 65% had metastatic disease. There were 184 deaths (10.3%) on study. For low, intermediate and high Risk Score, there were 8.1%, 11.2%, and 32.5% deaths, respectively. In multivariate analyses, the Risk Score remained an independent predictor of death (OR for high/intermediate vs. low score = 1.70, p = 0.0027), in addition to age (OR for each incremental year = 1.03, p = 0.0014), presence of metastatic disease (OR = 3.28, p < 0.0001), and ECOG performance status ≥2 (OR = 3.85, p < 0.0001). VTE itself was not associated with death. Conclusions: This prospective global cohort study demonstrates that the Risk Score is prognostic of early mortality in CRC patients, in addition to age, stage, and performance status. Intermediate or high-risk patients, as defined by the Risk Score, may benefit from additional interventions aimed at reducing early mortality.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".