NCI Rectal-Anal Task Force consensus recommendations for design of clinical trials in rectal cancer
Bibliographic record
Abstract
The optimal management of locally advanced rectal cancer is rapidly evolving. The National Cancer Institute Rectal-Anal Task Force convened an expert panel to develop consensus on the design of future clinical trials of patients with rectal cancer. A series of 82 questions and subquestions, which addressed radiation and neoadjuvant therapy, patient perceptions, rectal cancer populations of special interest, and unique design elements, were subject to iterative review using a Delphi analytical approach to define areas of consensus and those in which consensus is not established. The task force achieved consensus on several areas, including the following: 1) the use of total neoadjuvant therapy with long-course radiation therapy either before or after chemotherapy, as well as short-course radiation therapy followed by chemotherapy, as the control arm of clinical trials; 2) the need for greater emphasis on patient involvement in treatment choices within the context of trial design; 3) efforts to identify those patients likely, or unlikely, to benefit from nonoperative management or minimally invasive surgery; 4) investigation of the utility of circulating tumor DNA measurements for tailoring treatment and surveillance; and 5) the need for identification of appropriate end points and recognition of challenges of data management for patients who enter nonoperative management trial arms. Substantial agreement was reached on priorities affecting the design of future clinical trials in patients with locally advanced rectal cancer.
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 | 0.672 | 0.677 |
| Meta-epidemiology (narrow) | 0.004 | 0.005 |
| Meta-epidemiology (broad) | 0.008 | 0.021 |
| Bibliometrics | 0.018 | 0.018 |
| Science and technology studies | 0.008 | 0.008 |
| Scholarly communication | 0.015 | 0.010 |
| Open science | 0.020 | 0.012 |
| Research integrity | 0.026 | 0.032 |
| Insufficient payload (model declined to judge) | 0.010 | 0.010 |
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".