Prophylactic cranial irradiation in small cell lung cancer patients in the era of magnetic resonance imaging: A systematic review and meta-analysis.
Bibliographic record
Abstract
e20636 Background: Patients with small cell lung cancer (SCLC) are at a particularly high risk for the development of brain metastases. Current guidelines recommend prophylactic cranial irradiation (PCI) for these patients to prevent brain metastases and prolong overall survival (OS), although the clinical evidence for recommendations stems from an era without routine use of brain imaging. We performed a systematic review and meta-analysis of all available studies reporting on PCI for SCLC patients with minimal inclusion restrictions to assesses the efficacy of PCI in patients with limited disease (LD) and extensive disease (ED) SCLC and focus on the impact of routine brain imaging. Methods: A literature search for studies reporting on PCI in SCLC patients performed in EMBASE, MEDLINE, CENTRAL, and grey literature sources identified 4,783 studies. Random-effects meta-analyses pooled hazard ratios (HR) for overall survival (OS) between PCI and no intervention groups. Results: 208 individual studies reported on outcomes related to PCI with 175 studies assessing survival differences associated with PCI, and 87 of these being amenable to meta-analysis. The majority (n = 79) were retrospective cohort studies. PCI was associated with improved OS in all SCLC patients (HR 0.60; 95% CI 0.55-0.65; n = 87 studies; n = 50,339 patients; I2= 77%), as well as in cohorts exclusively consisting of LD patients (HR 0.60; 95% CI 0.54-0.66; n = 58 studies; n = 22,417 patients; I2= 76%) or ED patients (HR 0.63; 95% CI 0.53-0.75; n = 23 studies; n = 24,997; I2= 75%). Only eight studies confirmed absence of IMD at restaging using magnetic resonance imaging in all patients and found OS no longer to be in favour of PCI (HR 0.75; 95% CI 0.50-1.12; n = 1,318 patients; I2= 77%). Pooled OS from randomized controlled trials was not associated with PCI (HR 0.88; 95% CI 0.65-1.12; n = 5 studies; n = 925 patients; I2= 62.5%). Among studies not amenable to meta-analysis for OS, 4 radiographically confirmed absence of IMD, but none found OS to be in favour of PCI. Conclusions: Administration of PCI is associated with a significant OS benefit, but not when considering studies that radiographically confirmed absence of IMD at restaging or randomized controlled trials, suggesting that patient selection may be contributing to this observation.
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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 | 0.010 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.037 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".