A Patient-Level Data Meta-analysis of the Abscopal Effect
Why this work is in the frame
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Bibliographic record
Abstract
Purpose: The abscopal effect is defined when a form of local therapy causes tumor regression of both the target lesion and any untreated tumors. Herein cases of the abscopal effect were systematically reviewed and a patient-level data analysis was performed for clinical predictors of both duration of response and survival. Methods and Materials: The Population, Intervention, Control, Outcome, Study (PICOS) design approach, Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) literature selection process, and Meta-analysis of Observational Studies in Epidemiology (MOOSE) were used to find articles published before September 2019 in MEDLINE/PubMed and Google Scholar. Inclusion criteria were (1) population: patients with reported abscopal response; (2) intervention: documented treatment(s); (3) control: none; (4) outcomes: overall and progression-free survival; and (5) setting: retrospective case reports. Time from treatment until abscopal response and time from abscopal response until progression/death were calculated. Univariate and multivariate analyses were conducted for survival outcomes. Results: Fifty studies (n = 55 patients) were included. Median age was 65 years (interquartile range [IQR], 58-70) and 62% were male. Fifty-four (98%) patients received radiation therapy, 34 (62%) received radiation therapy alone, 5 (9.1%) underwent surgery, 4 (7.3%) received chemotherapy, and 11 (20%) received immunotherapy. Median total dose was 32 Gy (IQR, 25.5-48 Gy) and median dose per fraction was 3 Gy (IQR, 2-7.2). Median time until abscopal response was 4 months (IQR, 1-5; min 0.5, max 24). At 5 years, overall survival was 63% and distant progression-free survival was 45%. No variables had statistical significance in predicting duration of response or survival. Conclusions: Almost all reported cases of the abscopal response are after radiation therapy; however, there are no known predictors of duration of response or survival in this population.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it