Excellence in oncology care (EIOC) consensus guidelines on integrating immunotherapy (IO) in resectable non-small cell lung cancer (NSCLC) for the Middle East and Indian subcontinent
Bibliographic record
Abstract
ABSTRACT The Excellence in Oncology Care (EIOC) 2023 Congress, held in Dubai, took place both in person and online. This annual event brought together oncologists from across the Middle East and the Indian subcontinent. A panel of 17 regional experts worked together to develop the first region-specific consensus guidelines. A survey was conducted among the panelists, followed by a preparatory meeting to discuss the results and formulate the guidelines. These guidelines were then presented and discussed at the congress. The panel addressed non-small cell lung cancer (NSCLC), focusing specifically on integrating immunotherapy in resectable NSCLC. The management of NSCLC is advancing, particularly in the early stages. For stages II to IIIA, adjuvant platinum-based chemotherapy is recommended, but new therapies are needed due to limited efficacy. Immunotherapy, including atezolizumab and pembrolizumab, is now standard for resected stage I-III NSCLC, though challenges in clinical uptake and biomarker testing persist. Comprehensive staging evaluation, including positron emission tomography-computed tomography, mediastinal assessment, and central nervous system screening, is advised. EGFR and ALK biomarker testing, along with multidisciplinary team discussions, is crucial. Adjuvant immunotherapy decisions should be guided by PD-L1 status, with atezolizumab or pembrolizumab recommended for 12 months. Neoadjuvant ICI therapy with chemotherapy is suggested for stages IB to IIIA/B NSCLC. The EIOC guidelines offer detailed insights into NSCLC management.
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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 | 0.040 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.006 | 0.006 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.002 | 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".