Impact of frailty on 5-year survival in patients older than 70 years undergoing colorectal surgery for cancer
Bibliographic record
Abstract
BACKGROUND: Frailty has been shown to be a good predictor of post-operative complications and death in patients undergoing gastrointestinal surgery. The aim of this study was to analyze the differences between frail and non-frail patients undergoing colorectal cancer surgery, as well as the impact of frailty on long-term survival in these patients. METHODS: A cohort of 149 patients aged 70 years and older who underwent elective surgery for colorectal cancer was followed-up for at least 5 years. The sample was divided into two groups: frail and non-frail patients. The Canadian Study of Health and Aging-Clinical Frailty Scale (CSHA-CFS) was used to detect frailty. The two groups were compared with regard to demographic data, comorbidities, functional and cognitive statuses, surgical risk, surgical variables, tumor extent, and post-operative outcomes, which were mortality at 30 days, 90 days, and 1 year after the procedure. Univariate and multivariate analyses were also performed to determine which of the predictive variables were related to 5-year survival. RESULTS: Out of the 149 patients, 96 (64.4%) were men and 53 (35.6%) were women, with a median age of 75 years (IQR 72-80). According to the CSHA-CFS scale, 59 (39.6%) patients were frail, and 90 (60.4%) patients were not frail. Frail patients were significantly older and had more impaired cognitive status, worse functional status, more comorbidities, more operative mortality, and more serious complications than non-frail patients. Comorbidities, as measured by the Charlson Comorbidity Index (p = 0.001); the Lawton-Brody Index (p = 0.011); failure to perform an anastomosis (p = 0.024); nodal involvement (p = 0.005); distant metastases (p < 0.001); high TNM stage (p = 0.004); and anastomosis dehiscence (p = 0.013) were significant univariate predictors of a poor prognosis on univariate analysis. Multivariate analysis of long-term survival, with adjustment for age, frailty, comorbidities and TNM stage, showed that comorbidities (p = 0.002; HR 1.30; 95% CI 1.10-1.54) and TNM stage (p = 0.014; HR 2.06; 95% CI 1.16-3.67) were the only independent risk factors for survival at 5 years. CONCLUSIONS: Frailty is associated with poor short-term post-operative outcomes, but it does not seem to affect long-term survival in older patients with colorectal cancer. Instead, comorbidities and tumor stage are good predictors of long-term survival.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 teacher head, 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".