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Association of HLA Antigen Mismatch With Risk of Developing Skin Cancer After Solid-Organ Transplant

2019· article· en· W2912515505 on OpenAlex
Yi Gao, Amanda R. Twigg, Ryutaro Hirose, Garrett R. Roll, Amy S. Nowacki, Edward V. Maytin, Allison T. Vidimos, Raja Rajalingam, Sarah T. Arron

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJAMA Dermatology · 2019
Typearticle
Languageen
FieldMedicine
TopicNonmelanoma Skin Cancer Studies
Canadian institutionsnot available
FundersUniversity of California, San DiegoUniversity of California, Los AngelesUniversity of PittsburghCleveland Clinic FoundationBrigham and Women's HospitalUniversity of MinnesotaYork UniversityUniversity of PennsylvaniaCleveland Clinic
KeywordsMedicineHuman leukocyte antigenSolid organOrgan transplantationImmunologyHistocompatibility TestingAntigenSkin cancerDermatologyCancerTransplantationInternal medicine

Abstract

fetched live from OpenAlex

Importance: Risk factors for the development of skin cancer after solid-organ transplant can inform clinical care, but data on these risk factors are limited. Objective: To study the association between HLA antigen mismatch and skin cancer incidence after solid-organ transplant. Design, Setting, and Participants: This retrospective cohort study is a secondary analysis of the multicenter Transplant Skin Cancer Network study of 10 649 adults who underwent a primary solid-organ transplant between January 1, 2003, and December 31, 2003, or between January 1, 2008, and December 31, 2008. These participants were identified through the Scientific Registry of Transplant Recipients standard analysis files, which contain data collected mostly by the Organ Procurement and Transplantation Network. Participants were matched to skin cancer outcomes by medical record review. This study was conducted from August 1, 2016, to July 31, 2017. Main Outcomes and Measures: The primary outcome was time to diagnosis of posttransplant skin cancer, including squamous cell carcinoma, melanoma, and Merkel cell carcinoma. The HLA antigen mismatch was calculated based on the 2016 Organ Procurement and Transplantation Network guidelines. Risk of skin cancer was analyzed using a multivariate Cox proportional hazards regression model. Results: In total, 10 649 organ transplant recipients (6776 men [63.6%], with a mean [SD] age of 51 [12] years) contributed 59 923 years of follow-up. For each additional mismatched allele, a 7% to 8% reduction in skin cancer risk was found (adjusted hazard ratio [HR], 0.93; 95% CI, 0.87-0.99; P = .01). Subgroup analysis found the protective effect of HLA antigen mismatch to be statistically significant in lung (adjusted HR, 0.70; 95% CI, 0.56-0.87; P = .001) and heart (adjusted HR, 0.75; 95% CI, 0.60-0.93; P = .008) transplant recipients but not for recipients of liver, kidney, or pancreas. The degree of HLA-DR mismatch, but not HLA-A or HLA-B mismatch, was the most statistically significant for skin cancer risk (adjusted HR, 0.85; 95% CI, 0.74-0.97; P = .01). Conclusions and Relevance: The HLA antigen mismatch appears to be associated with reductions in the risk of skin cancer after solid-organ transplant among heart and lung transplant recipients; this finding suggests that HLA antigen mismatch activates the tumor surveillance mechanisms that protect against skin cancer in transplant recipients and that skin cancer risk may be higher in patients who received a well-matched organ.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.095
Threshold uncertainty score0.452

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.005
GPT teacher head0.250
Teacher spread0.245 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it