Merkel cell carcinoma after solid organ transplant
Bibliographic record
Abstract
Merkel cell carcinoma (MCC) is a rare, aggressive neuroendocrine tumour with increased incidence in solid organ transplant recipients (SOTRs). This study provides the first systematic synthesis of current literature on the clinical characteristics, treatments and outcomes of MCC in SOTRs. A search of Ovid's Medline and Embase databases was conducted from inception to December 2023, following PRISMA 2020 guidelines (PROSPERO: CRD42024512388). Thirty studies were identified after abstract/title and full-text screening, with citation chaining identifying 18 additional articles. This yielded a total of 264 SOTR-MCC patients (Table 1), with 110 originating from a 2015 study by Clarke et al.1 Most were male (72.6%) and of European ancestry (92.8%). The median of median diagnostic age was 69 years, and the median of median post-transplant time was 62.8 months. Kidney transplants were the most common (64.4%), followed by cardiothoracic (20.1%) and liver transplants (11.4%). Primary tumour sites were predominantly located in the head and neck (49.1%) and upper limb (24.3%). Most patients were on two (42.6%) or three (51.5%) immunosuppressive drugs at diagnosis, commonly corticosteroids (34.6%), cyclosporine (23.0%) or azathioprine (19.4%). Post-diagnosis treatments included surgery (n = 64), radiation (n = 35) and chemotherapy (n = 20). Six studies reported standardized incidence ratios (SIRs) for SOTR-MCC. Of these, three examined SIRs across kidney, liver and cardiothoracic transplants; two focused on kidney transplants; one studied cardiothoracic transplant. The summary SIR for SOTR-MCC was 56.17 (95% CI 32.78–96.25; p < 0.0001) (Figure 1a), with the kidney subgroup showing a summary SIR of 67.90 (95% CI 44.41–103.82; p < 0.0001) (Figure 1b). While kidney transplants accounted for a large proportion of cases, this emphasis may stem from the relative frequencies of these transplants rather than characteristics associated with specific SOTs.2 A Swedish study found kidney transplants to have the lowest MCC SIR (52) compared to liver (182) and thoracic transplants (121).3 Variations in immunosuppressive intensity and characteristics may better explain variabilities in SIR estimates across SOT types. The role of immune status and immunosuppressive aetiology as predictors of overall survival (OS) in MCC has been well-established. A 2021 study by Yusuf et al. found the 3-year OS for SOTR-MCC patients to be 33%, which was lower than that of MCC patients with leukaemia (40.3%) or non-Hodgkin's lymphoma (52.1%).4 A proposed cause of MCC is the integration of Merkel cell polyomavirus (MCPyV) into the host genome, which disrupts the retinoblastoma pathway.5 However, while 72%–91% of immunocompetent MCC patients are MCPyV-positive, only 20%–33% of SOTR-MCC cases test positive.6, 7 A 2022 study by Ferrándiz-Pulido et al.6 found that SOTR-MCC tumours exhibit histological characteristics consistent with MCPyV-negative MCC. These recent findings suggest MCPyV may be less involved in the etiopathogenesis of SOTR-MCC than previously thought. Current SOTR-MCC treatment aligns with that of the general population, with surgery being the most common approach. However, a 2018 study found PD-1/PD-L1 immune checkpoint inhibitors to significantly improve OS for metastatic MCC patients.8 While PD-1/PD-L1 inhibitors are associated with acute rejection and graft loss in kidney transplants, reducing drug administration frequency has contributed to successful outcomes, suggesting they should still be considered for SOTR-MCC.9 Our findings highlight that male sex, European ancestry, older age and a prolonged post-transplant period are risk factors for SOTR-MCC. These trends are consistent with the Clarke et al. study, which remains the largest SOTR-MCC dataset to date. Further research is needed to validate these findings and elucidate how factors such as specific immunosuppressive medications and MCPyV status contribute to SOTR-MCC risk. None. The authors declare no conflicts of interest. Not applicable. Not applicable. The data that support the findings of this study are available from the corresponding author upon reasonable request.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.004 |
| 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".