SynthesisFrontiers in oncology2022
Risk Factors for Brain Metastases in Patients With Small Cell Lung Cancer: A Systematic Review and Meta-Analysis.
Synthesis in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 3 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
16 citing papers in PubMed, 3 syntheses or guidelines pooled it, 19 citations in OpenAlex.
- Pooled it
- Risk factors for brain metastasis in lung cancer: an umbrella review of systematic reviews and meta-analyses.BMJ open · 2025Pooled it
- Risk Factors for Brain Metastases in Patients With Small Cell Lung Cancer: A Systematic Review and Meta-Analysis.Frontiers in oncology · 2022Pooled it
- BraMARS: An Interpretable Histopathology-Driven Deep Learning Model for Brain Metastasis Risk Stratification in Surgically Resected Limited-Stage SCLC.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Small Cell Lung Cancer in Transition: Recent Advances in Biology, Treatment, and Precision Medicine.Cancers · 2026Review
- Machine Learning-Based Prediction of Brain Metastasis at Initial Diagnosis in Small-Cell Lung Cancer: Model Development and SHAP Interpretation Study.Cancer reports (Hoboken, N.J.) · 2026Article
- Comparison of 6 cycles with 4 cycles of chemotherapy and atezolizumab in the first-line treatment of ES-SCLC: a retrospective multicenter analysis.The oncologist · 2026Article
- Esophageal Small Cell Carcinoma: From Bench Discoveries to Bedside Therapeutics.International journal of biological sciences · 2026Review
- Current and Emerging Therapeutic Strategies for Limited- and Extensive-Stage Small-Cell Lung Cancer.Medical sciences (Basel, Switzerland) · 2025Review
- Exploring the Role of Peritumoral Edema in Predicting Lung Cancer Subtypes Through T2-FLAIR Digital Subtraction Imaging of Metastatic Brain Tumors.Diagnostics (Basel, Switzerland) · 2025Article
- Real-world outcomes of prophylactic cranial irradiation utilization and efficacy for patients with extensive-stage small cell lung cancer treated with consolidative thoracic radiotherapy.Clinical and translational radiation oncology · 2025Article
- Advancements in consolidative thoracic radiotherapy following first-line immunotherapy in conjunction with chemotherapy for extensive-stage small cell lung cancer.Frontiers in immunology · 2025Review
- Machine learning-based prediction model for brain metastasis in patients with extensive-stage small cell lung cancer.Scientific reports · 2024Article
- Construction, validation, and visualization of a web-based nomogram to predict overall survival in small-cell lung cancer patients with brain metastasis.Cancer causes & control : CCC · 2024Article
- Article
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 5 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The use of prophylactic cranial irradiation (PCI) for small cell lung cancer (SCLC) patients is controversial. Risk factors for brain metastasis (BM) development are largely lacking, hampering personalized treatment strategies. This study aimed to identify the possible risk factors for BM in SCLC.We systematically searched the Pubmed database (1 January 1995 to 18 January 2021) according to the PRISMA guidelines. Eligibility criteria: studies reporting detailed BM data with an adequate sample size (randomized clinical trials [RCTs]: N ≥50; non-RCTs: N ≥100) in patients with SCLC. We summarized the reported risk factors and performed meta-analysis to estimate the pooled hazard ratios (HR) if enough qualified data (i.e., two or more studies; the same study type; the same analysis method; and HRs retrievable) were available. In total, 61/536 records were eligible (18 RCTs and 39 non-RCTs comprising 13,188 patients), in which 57 factors were reported. Ten factors qualified BM data for meta-analysis: Limited stage disease (LD) (HR = 0.34, 95% CI: 0.17-0.67; P = 0.002) and older age (≥65) (HR = 0.70, 95% CI: 0.54-0.92; P = 0.01) were associated with less BM; A higher T stage (≥T3) (HR = 1.72, 95% CI: 1.16-2.56; P = 0.007) was a significant risk factor for BM. Male sex (HR = 1.24, 95% CI: 0.99-1.54; P = 0.06) tended to be a risk factor, and better PS (0-1) (HR = 0.66, 95% CI: 0.42-1.02; P = 0.06) tended to have less BM. Smoking, thoracic radiotherapy dose were not significant (P >0.05). PCI significantly decreased BM (P <0.001), but did not improve OS in ED-SCLC (P = 0.81). A higher PCI dose did not improve OS (P = 0.11). The impact on BM was conflicting between Cox regression data (HR = 0.59, 95% CI: 0.26-1.31; P = 0.20) and competing risk regression data (HR = 0.74, 95% CI: 0.55-0.99; P = 0.04). Compared to M0-M1a, M1b was a risk factor for OS (P = 0.01) in ED-SCLC, but not for BM (P = 0.19). As regular brain imaging is rarely performed, high-quality data is lacking. Other factors such as N-stage and blood biomarkers had no qualified data to perform meta-analysis. In conclusion, younger age, higher T stage, and ED are risk factors for BM, suggesting that PCI should be especially discussed in such cases. Individual patient data (IPD) meta-analysis and well-designed RCTs are needed to better identify more risk factors and further confirm our findings.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.