Prognostic Value of Response Evaluation Using PSMA PET/CT in Patients with Metastatic Prostate Cancer (RECIP 1.0): A Systematic Review and Meta-analysis
Bibliographic record
Abstract
RATIONALE AND OBJECTIVES: Recently, the Response Evaluation Using PSMA PET/CT in Patients with Metastatic Castration-Resistant Prostate Cancer (RECIP 1.0) was proposed to better evaluate treatment response in prostate cancer patients using PET/CT with prostate-specific membrane antigen (PSMA) than more traditional approaches like metabolic PET evaluation response criteria in solid tumor (PERCIST 1.0). This system showed promising results in single-center studies. We aim to evaluate the prognostic performance of RECIP 1.0 in assessing treatment outcomes in metastatic prostate cancer patients with a systematic review and meta-analysis. MATERIALS AND METHODS: Searches were conducted across PubMed/MEDLINE, EMBASE, and Web of Science databases through March 2024. Only studies involving patients with metastatic prostate cancer who underwent PSMA PET/CT to assess therapeutic response and who were evaluated using the RECIP 1.0 criteria were included. Pooled hazard ratios for mortality and concordance indices (c-index) of RECIP were assessed. A secondary analysis compared RECIP 1.0 to PSMA PET Progression Criteria (PPP) in head-to-head studies. RESULTS: From an initial 553 reports, eight met the eligibility criteria after full-text review (n=516 patients) and six underwent quantitative analysis. RECIP 1.0 significantly differentiated between disease progression and non-progression in terms of mortality risk (HR: 3.48; 95% CI: 2.64-4.59). A sub-analysis of three studies with 174 patients demonstrated a pooled c-index of 0.68 (95% CI: 0.65-0.71). Comparison involving 224 patients from three studies indicated a non-significant trend favoring RECIP 1.0 over PPP. CONCLUSION: RECIP 1.0 offers robust prognostic value for assessing metastatic prostate cancer treatment outcomes.
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How this classification was reachedexpand
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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.010 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".