The management of patients with T1 adenocarcinoma of the low rectum: An updated decision analysis.
Bibliographic record
Abstract
645 Background: Patients with T1 adenocarcinoma of the low rectum are faced with a choice between Transanal Local Excision (TLE) and Abdonimoperineal Resection (APR). Fundamentally a tradeoff between quantity and quality of life, this problem is well-suited to decision analysis. A previous decision analysis examined this issue in 1999, but subsequent case series have reported TLE recurrence rates higher than that study considered plausible. Decision analytic techniques have also evolved by incorporating Markov modeling, which better accounts for the temporal aspects of the problem, and microsimulation, which allows for greater flexibility. Methods: We developed a Markov-type microsimulation to evaluate the decision between APR and TLE in T1 adenocarcinoma of the low rectum. We used the software package 'R' and have made all computer code freely available for full transparency. Critical parameters such as transition rates and utilities were elicited by systematic literature reviews and expert opinion. Conflicting values were resolved by weighted averaging and sensitivity analyses. Results: On average, selecting TLE over APR for T1 rectal cancer resulted in a loss of 0.53 years of life expectancy but a gain of 0.97 quality-adjusted life years; hence, TLE was considered the preferable option in the majority of patients. APR was preferred if and only if the patient was unwilling to yield 7% of his or her life expectancy to avoid a permanent stoma. This transition point shifted depending on the anticipated risk of recurrence after TLE. Sensitivity analysis indicated robustness of our findings. Conclusions: Though performing an APR for T1 adenocarcinoma of the low rectum does provide an extra six months of life expectancy, a TLE is the preferable approach for the majority of patients when quality-of-life is taken into consideration. The decision in an individual patient's case can be facilitated by tumour risk-stratification and by ascertaining the patient's willingness to yield life expectancy to avoid a permanent stoma.
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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 | 0.016 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.007 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".