Follow-Up Imaging Guidelines for Patients with Stage III Unresectable NSCLC: Recommendations Based on the PACIFIC Trial
Bibliographic record
Abstract
The PACIFIC trial showed a survival benefit with durvalumab through five years in stage III unresectable non-small cell lung cancer (NSCLC). However, optimal use of imaging to detect disease progression remains unclearly defined for this population. An expert working group convened to consider available evidence and clinical experience and develop recommendations for follow-up imaging after concurrent chemotherapy and radiation therapy (CRT). Voting on agreement was conducted anonymously via online survey. Follow-up imaging was recommended for all suitable patients after CRT completion regardless of whether durvalumab is received. Imaging should occur every 3 months in Year 1, at least every 6 months in Year 2, and at least every 12 months in Years 3-5. Contrast computed tomography was preferred; routine brain imaging was not recommended for asymptomatic patients. The medical oncologist should follow-up during Year 1 of durvalumab therapy, with radiation oncologist involvement if pneumonitis is suspected; medical and radiation oncologists can subsequently alternate follow-up. Some patients can transition to the family physician/community primary care team at the end of Year 2. In Years 1-5, patients should receive information regarding smoking cessation, comorbidity management, vaccinations, and general follow-up care. These recommendations provide guidance on follow-up imaging for patients with stage III unresectable NSCLC whether or not they receive durvalumab consolidation therapy.
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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 | 0.032 | 0.058 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".