Clinical factors influencing retreatment with anti-PD-(L)1 therapies after treatment in early-stage cancers: a modified Delphi consensus study
Bibliographic record
Abstract
Anti-programmed death (ligand) 1 (anti-PD-(L)1) therapies were first introduced in the metastatic setting and have since been approved and reimbursed for treating early-stage cancers in the adjuvant, perioperative, and neoadjuvant settings in many cancer types. Current evidence supporting anti-PD(L)-1 retreatment after relapse with prior neoadjuvant and/or adjuvant anti-PD(L)1 therapy is limited and inconclusive. There is no guidance for clinicians on how and when to retreat with anti-PD-(L)1 therapies when anti-PD-(L)1 therapy was administered in the neoadjuvant and/or adjuvant setting. This study aimed to reach consensus on factors to guide decision-making regarding retreatment with anti-PD-(L)1 therapies after prior therapy with an anti-PD-(L)1 agent. This modified Delphi study consisted of a clinician survey across 10 countries followed by three real-time virtual Delphi panels involving clinical experts who had completed the survey. Clinical experts were experienced in using anti-PD-(L)1 treatments in early-stage cancers and/or as retreatment of patients with recurrences following early-stage treatment with anti-PD-(L)1 therapies. Of 28 clinicians providing survey responses, 20 participated in one of three Delphi panels. There was consensus that retreatment can be defined as 'repeated treatment with the same therapeutic class following relapse after or during neoadjuvant and/or adjuvant treatment.' All three panels agreed that decisions around retreatment should consider 'prior immune-related adverse events/toxicity,' 'time-related factors' (eg, time since completion of full treatment course and since discontinuation) and 'previous patient response' (often referred to by clinicians as tumor response, which may have reflected their experience with metastatic disease). Other factors identified as important included country-specific practices, treatment availability, and reimbursement. Generally, the clinical experts considered that retreatment could be considered from ≥3 to 6 months after stopping initial anti-PD-(L)1 treatment, or from ≥6 months after relapse/recurrence. In conclusion, clinicians across different regions recognized a role for retreating patients with anti-PD-(L)1 therapies after initial anti-PD-(L)1 treatment for early-stage cancers. Consensus was reached on some factors to consider regarding whether and when to retreat, although differences in clinical practice between countries/geographical regions made it difficult to achieve consensus for some more nuanced elements of retreatment. Further evidence could help better inform retreatment decisions.
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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 | 0.120 | 0.158 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".