Chest Wall Toxicity after Stereotactic Radiation in Early Lung Cancer: A Systematic Review
Bibliographic record
Abstract
Background: Radiation-induced chest wall pain (CWP) and rib fracture (RF) are late adverse effects after stereotactic body radiation therapy (SBRT) for stage i non-small-cell lung cancer (NSCLC); however, the literature about their incidence and risk factors shows variability. We performed a systematic review to determine the pooled incidence of CWP and RF in the relevant population. Methods: A literature search using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines considered English publications in MEDLINE and EMBASE from January 1996 to August 2017. Abstracts were screened, followed by full-text review and data extraction. Results: The database searches identified 547 records. Twenty-eight publications comprising 3892 patients met the inclusion criteria. Median reported ages and follow-up durations fell into the ranges 67–82 years and 12–84 months. Prescriptions fell into the range of 40–70 Gy in 3–10 fractions. Despite study heterogeneity, the pooled incidences of CWP and RF were estimated to be 8.94% and 5.27% respectively. Nineteen studies reported cwp grade: 58 of 308 patients (18.8%) experienced grades 3–4 CWP (no grade 5 events reported). Thirteen studies reported RF grade: grades 3–4 RF were observed in 9 of 113 patients (7.96%). A high chest wall V30 was an important predictor of CWP and RF. Conclusions: In patients with stage i nsclc, rates of CWP and RF after SBRT are low; however, tumour location, accurate toxicity reporting, and dose–fractionation schemes might alter those rates. Prospective correlation with dosimetry and quality of life assessment will further improve the understanding of CWP and RF after sbrt.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.010 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".