Consistency of recommendations for the diagnosis and treatment of non-small cell lung cancer: a systematic review
Bibliographic record
Abstract
BACKGROUND: To systematically assess the consistency of recommendations regarding diagnosis and treatment of non-small cell lung cancer (NSCLC) in clinical practice guidelines (CPGs). METHODS: We systematically searched relevant literature databases and websites to identify CPGs related to NSCLC. We extracted the general characteristics of the included guidelines and their recommendations and descriptively compared and analyzed the consistency of recommendations across the guidelines. RESULTS: A total of 28 NSCLC guidelines were retrieved. The recommendations covered mainly diagnosis and treatment. The recommendations in the guidelines differed substantially in various topics, such as the application of positron emission tomography (PET) and the classification of stage III. Fourteen guidelines divided stage III into two types: operable and inoperable; and the remaining 14 guidelines into three sub-stages IIIA, IIIB and IIIC. Recommendations regarding the treatment in stage III were relatively inconsistent. In driver gene (EGFR, ALK, ROS1) positive patients, targeted therapy was the most common recommendation for first-line treatment, but recommendations regarding second-line treatment varied according to the site of the mutation. In driver gene negative patients, immunotherapy was the most frequently recommended option as both first- and second-line treatment, followed by chemotherapy. DISCUSSION: A number of countries are devoting themselves to develop NSCLC guidelines and the process of updating guidelines is accelerating, yet recommendations between guidelines are not consistent. We adopted a systematic review method to systematically search and analyze the NSCLC guidelines worldwide. We objectively reviewed the differences in recommendations for NSCLC diagnosis and treatment between the guidelines. Inconsistency of recommendations across guidelines can result from multiple potential reasons. Such as, the guidelines developed time, different countries and regions and many more. Poor consistency across CPGs can confuse the guideline users, and we therefore advocate paying more attention to examining the controversies and updating guidelines timely to improve the consistency among CPGs. Our study had also several limitations, we limited the search to CPGs published in Chinese or English, the interpretation of recommendations is inherently subjective, we did not evaluate the details of the clinical content of the CPG recommendations. Our research presents the current status of NSCLC guidelines worldwide and give the opportunity to pay more attention to the existing gaps. Further investigations should determine the reasons for inconsistency, the implications for recommendation development, and the role of synthesis across recommendations for optimal guidance of clinical care treatment. With the continuous revision and update of the guidelines, we are confident that future guidelines will be formulated with higher quality to form clear, definite and consistent recommendations for NSCLC diagnosis and treatment.
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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 | 0.098 | 0.430 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.028 | 0.023 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| 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".