Incidence, mortality and survival of Merkel cell carcinoma: a systematic review of population-based studies
Bibliographic record
Abstract
BACKGROUND: Merkel cell carcinoma (MCC) is a rare, aggressive skin cancer that most commonly occurs in ultraviolet-exposed body sites. The epidemiology of MCC in different geographies and populations is not well characterized. OBJECTIVES: The objective of this systematic review is to summarize evidence on the incidence, mortality and survival rates of MCC from population-based studies. METHODS: We searched MEDLINE, Embase, and the Cochrane Central Register of Controlled Trials from database inception to 6 June 2023. No geographic, age or date exclusions were applied. We included population-based studies of MCC that reported the incidence, survival or mortality rate, and also considered systematic reviews. A data-charting form was created and validated to identify variables to extract. Two reviewers then independently charted the data for each included study with patient characteristics, and estimates of incidence rate, mortality rate, and survival rate and assessed the quality of included studies using the Joanna Briggs Institute Checklist for Prevalence studies, Newcastle-Ottawa Scale and Assessment of Multiple Systematic Reviews. We abstracted age-, sex-, stage- and race-stratified outcomes, and synthesized comparisons between strata narratively and using vote counting. We assessed the certainty of evidence for those comparisons using the Grading of Recommendations, Assessments, Developments and Evaluations framework. RESULTS: We identified 11 472 citations, of which 52 studies from 24 countries met our inclusion criteria. Stage I and the head and neck were the most frequently reported stage and location at diagnosis. The incidence of MCC is increasing over time (high certainty), with the highest reported incidences reported in southern hemisphere countries [Australia (2.5 per 100 000); New Zealand (0.96 per 100 000) (high certainty)]. Male patients generally had higher incidence rates compared with female patients (high certainty), although there were some variations over time periods. Survival rates varied, with lower survival and/or higher mortality associated with male sex (moderate certainty), higher stage at diagnosis (moderate-to-high certainty), older age (moderate certainty), and immunosuppression (low-to-moderate certainty). CONCLUSIONS: MCC is increasing in incidence and may increase further given the ageing population of many countries. The prognosis of MCC is poor, particularly for male patients, those who are immunosuppressed, and patients diagnosed at higher stages or at an older age.
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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 | 0.013 | 0.068 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.012 |
| Bibliometrics | 0.015 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".