Outcomes of patients with metastatic phaeochromocytoma and paraganglioma: A systematic review and meta‐analysis
Bibliographic record
Abstract
OBJECTIVE: The outcomes of patients with metastatic phaeochromocytoma (PHEO) and paraganglioma (PGL) are unclear. We performed a systematic review and meta-analysis of baseline characteristics and mortality rates of patients with metastatic PHEO and PGL (PPGL). DESIGN: Ovid MEDLINE In-Process & Other Non-Indexed Citations, Ovid MEDLINE, Ovid EMBASE, Ovid Cochrane Central Register of Controlled Trials, Ovid Cochrane Database of Systematic Reviews, Scopus, Web of Science, and references of key articles were searched from inception to 2016. PATIENTS: Studies comprised ≥20 patients with metastatic PPGL and reported baseline characteristics and follow-up data. MEASUREMENTS: Reviewers extracted standardized data and assessed risk of bias using a modified Newcastle-Ottawa tool. Random-effects meta-analysis was used to pool event rates across studies. RESULTS: Twenty retrospective noncomparative studies reported on 1338 patients with metastatic PHEO (685/1296, 52.9%) and PGL (611/1296, 47.1%), diagnosed at a mean age of 43.9 ± 5.2 years. Mean follow-up was 6.3 ± 3.2 years. Of 532 patients with reported data, 40.4% had synchronous metastases. Five-year (7 studies, n = 738) and 10-year (2 studies, n = 55) mortality rates for patients with metastatic PPGL were 37% (95% CI, 24%-51%) and 29% (95% CI, 17%-42%), respectively. Higher mortality was associated with male sex (RR 1.50; 95% CI, 1.11-2.02) and synchronous metastases (RR 2.43; 95% CI, 1.01-5.85). CONCLUSIONS: Available low-quality evidence from heterogeneous studies suggests low mortality rates of patients with metastatic PPGL. Male sex and synchronous metastases correlated with increased mortality. The outcomes of patients with metastatic PPGL have been inadequately assessed, indicating the need for carefully planned prospective studies.
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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 | 0.012 | 0.029 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.039 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".