Validity of skin cancer malignancy reporting to the Organ Procurement Transplant Network: A cohort study

External Validation of the Skin and UV Neoplasia Transplant Risk Assessment Calculator (SUNTRAC) in a Large European Solid Organ Transplant Recipient Cohort

Importance

The Skin and UV Neoplasia Transplant Risk Assessment Calculator (SUNTRAC) tool has been developed in the US to facilitate the identification of solid organ transplant recipients (SOTRs) at a higher risk of developing skin cancer. However, it has not yet been validated in populations other than the one used for its creation.

Objective

To provide an external validation of the SUNTRAC tool in different SOTR populations.

Design, Setting, and Participants

This retrospective external validation prognostic study used data from a prospectively collected cohort of European SOTRs from transplant centers at teaching hospitals in the Netherlands (1995-2016) and Spain (2011-2021). Participants were screened and followed up at dermatology departments. Data were analyzed from September to October 2021.

Main Outcomes and Measures

The discrimination ability of the SUNTRAC tool was assessed via a competing risk survival analysis, cumulative incidence plots, and Wolbers concordance index. Calibration of the SUNTRAC tool was assessed through comparison of projected skin cancer incidences. Skin cancer diagnoses included squamous cell carcinoma, basal cell carcinoma, melanoma, and Merkel cell carcinoma.

Results

A total of 3421 SOTRs (median age at transplant, 53 [quartile 1: 42; quartile 3: 62] years; 2132 [62.3%] men) were assessed, including 72 Asian patients (2.1%), 137 Black patients (4.0%), 275 Latinx patients (8.0%), 109 Middle Eastern and North African patients (3.2%), and 2828 White patients (82.7%). With a total of 23 213 years of follow-up time, 603 patients developed skin cancer. The SUNTRAC tool classified patients into 4 groups with significantly different risks of developing skin cancer during follow-up. Overall, the relative rate for developing skin cancer estimated using subdistribution hazard ratios (SHRs) and using the low-risk group as the reference group, increased according to the proposed risk group (medium-risk group: SHR, 6.8 [95% CI, 3.8-12.1]; P < .001; high-risk group: SHR, 15.9 [95% CI, 8.9-28.4]; P < .001; very-high-risk group: SHR, 54.8 [95% CI, 29.1-102.9]; P < .001), with a concordance index of 0.72. Actual skin cancer incidences were similar to those predicted by the SUNTRAC tool (5-year skin cancer cumulative incidence for medium-risk group: predicted, 6.2%; observed, 7.0%).

Conclusions and Relevance

The findings of this external validation prognostic study support the use of the SUNTRAC tool in European populations for stratifying SOTRs based on their skin cancer risk and also detecting patients at a high risk of developing skin cancer. This can be helpful in prioritizing and providing better screening and surveillance for these patients.

Differences in Skin Cancer Rates by Transplanted Organ Type and Patient Age After Organ Transplant in White Patients

Importance

Although it is known that patients with thoracic organ transplants develop skin cancer more frequently than those who receive nonthoracic organ transplants, patterns of risk for subsequent skin cancers are unknown.

Objective

To further characterize organ transplant recipients who develop multiple skin cancers and assess for patterns of development of additional skin cancers beyond the first skin cancer diagnosis by patient age and transplanted organ type.

Design, Setting, and Participants

This cohort study used validated electronic health record-based data from a single tertiary care academic medical center to identify 5129 solid organ transplant recipients who underwent transplant surgery between 1992 and 2017 and were older than 18 years at the time of transplant. The cohort was limited to White patients because they have the highest skin cancer risk based on phenotype. The mean follow-up was 6.6 years. Data were analyzed June 9, 2021, to May 31, 2022.

Main Outcomes and Measures

Differences in rates of skin cancer development for first and subsequent skin cancers were measured using t test or analysis of variance and χ2 tests for continuous and categorical variables. Rates of skin cancer development were compared based on organ type and patient age at transplant using Fine-Gray tests and cumulative incidence plots.

Results

A total of 5129 organ transplant recipients (mean [SD] age, 51.3 [12.9] years; 3287 men [64.1%]) were included. Of these, 695 patients (13.6%) had development of at least 1 skin cancer, with 6842 skin cancers identified in the cohort overall. Compared with liver transplant recipients, heart, lung, or kidney recipients were more likely to develop at least 1 skin cancer (χ2 test, 25.6; df, 4; P < .001). There was no significant difference by transplanted organ type in the rate of developing a second or third skin cancer; however, the age at transplant was associated with the time to developing a second (χ2 test, 20.4; df, 4; P < .001) or third (χ2 test, 10.9; df, 4; P < .02) skin cancer.

Conclusions and Relevance

This cohort study found that there was no difference by organ type for development of subsequent skin cancers in organ transplant recipients, and recipients of all organ types developed additional skin cancers at high rates after the initial skin cancer.

Risks of Multiple Skin Cancers in Organ Transplant Recipients: A Cohort Study in 2 Administrative Data Sets

Importance

There are limited reports on the risks of multiple primary skin cancers in organ transplant recipients (OTRs).

Objective

To determine the risks over time and risk factors for OTRs developing (1) any skin cancer posttransplant, (2) a subsequent skin cancer after the first posttransplant skin cancer in the data sets used in the study, and (3) 10 or more skin cancers.

Design, Setting, and Participants

This retrospective cohort study used data from Optum deidentified electronic health record data set (7.7 million patients) and Truven Health MarketScan insurance claims data set (161 million patients) from 2007 to 2017. Skin cancers were identified using diagnosis plus treatment codes for basal cell carcinoma, squamous cell carcinoma, and melanoma; OTRs were identified using 4 or more diagnosis codes for organ transplant. Data analysis took place from January 1, 2007, to December 31, 2017.

Main Outcomes and Measures

Cumulative risks of (1) any skin cancer treatment posttransplant, (2) a subsequent skin cancer treatment after the first posttransplant skin cancer treatment in our data, and (3) 10 or more skin cancer treatments in OTRs. A Wei-Lin-Weissfeld marginal model was used to evaluate risk factors for any skin cancer.

Results

A total of 7390 OTRs in Optum and 133 651 in MarketScan were identified, 4.5% and 13.3% of which had had at least 1 skin cancer treatment, respectively. At 2 years after the initial posttransplant skin cancer in the data sets, OTRs had a 44.0% to 57.0% risk of a subsequent skin cancer treatment and a 3.7% to 6.6% risk of having 10 or more skin cancer treatments. Statistically significant risk factors for any skin cancer included age, history of skin cancer, and history of actinic keratosis in both data sets, and male sex and thoracic transplant in MarketScan.

Conclusions and Relevance

In this retrospective cohort study, approximately half of the OTRs who developed at least 1 posttransplant skin cancer developed a subsequent skin cancer within 2 years, and approximately 1 in 20 developed 10 or more skin cancers. Identifying OTRs at highest risk for multiple primary skin cancers may help target strategies for prevention and early detection.

Cohort and Nested Case-Control Study of Cutaneous Squamous Cell Carcinoma in Solid Organ Transplant Recipients, by Medication

BACKGROUND

Knowledge is needed about squamous cell carcinoma (cSCC) risk in solid organ transplant recipients (SOTRs) using contemporary immunosuppressive regimens.

OBJECTIVE

Evaluate risk of cSCC in relation to medications used by SOTRs.

METHODS

The cohort and nest case-control study included 3,308 SOTRs and 65,883 persons without transplantation during 2009-2019. Incident cSCC was identified from pathology data and medications from pharmacy data. Adjusted hazard ratios (HR) and 95% confidence intervals (CI) were estimated using Cox proportional hazards analysis, with voriconazole examined as a time-dependent variable.

RESULTS

The annual incidence of cSCC was 1.69% in SOTRs and 0.30% in persons without transplantation. The adjusted HR of cSCC associated with lung transplant was 14.83 (CI 9.85-22.33) for lung and 6.53 to 10.69 for other organs. Risk in Latinx persons was higher than in other non-white groups. Among lung recipients, the HR was 1.14 for each month of voriconazole use (95% CI: 1.04-1.26). Azathioprine use for ≥7 months, relating to mycophenolate mofetil intolerance, was associated with 4.22-fold increased risk of cSCC (95% CI 1.90-9.40). Belatacept and other immunsuppressive medications were not associated with risk.

LIMITATIONS

The number of events was somewhat small.

CONCLUSIONS

Knowledge of risks and benefits in diverse patients can translate to care improvements.

Risk Prediction Model for Basal Cell Carcinoma in Cardiac Allograft Recipients

BACKGROUND

Basal cell carcinoma (BCC) is the second most common skin cancers in posttransplant patients. Long-term immunosuppression predisposes the patients to higher risk. This study was undertaken to develop a risk prediction model using the United Network for Organ Sharing (UNOS) database.

MATERIALS AND METHODS

Heart transplant recipients (2000~2015) from the UNOS database were analyzed. The Cox proportional hazards model was applied to screen the predictors associated with the development of BCC. Stepwise forward selection with Akaike information criterion was done to obtain the multivariate model. Area under the curve was derived from the receiver operating characteristics curve to assess the quality of the prediction model. A risk scoring system was developed to stratify patients into different risk groups, and the occurrence rates of posttransplant BCC among different groups were compared.

RESULTS

There were 24,374 patients who received heart transplantation within this study period, and 1211 recipients have been reported with BCC. The multivariate model provides area under the curves at 5, 8, and 10 years posttransplant of 0.77, 0.76, and 0.76, respectively, in the derivation set and 0.75, 0.74, and 0.74, respectively, in the validation set. The predicted and observed probabilities of developing BCC in 5 years agree well across different risk groups. Kaplan-Meier survival curves were generated, which demonstrate significant differences between subjects in different risk groups.

CONCLUSION

A risk prediction model has been generated for the first time for BCC with a c-statistic of ≥0.74 in both derivation and validation sets, making it a good tool for risk stratification.

Risk prediction model for cutaneous squamous cell carcinoma in adult cardiac allograft recipients

BACKGROUND

Heart transplant recipients are at higher risk of developing skin cancer than the general population due to the long-term immunosuppression treatment. Cancer has been reported as one of the major causes of morbidity and mortality for patients after heart transplantation. Among different types of skin cancers, cutaneous squamous cell carcinoma (cSCC) is the most common one, which requires timely screening and better management.

AIM

To identify risk factors and predict the incidence of cSCC for heart transplant recipients.

METHODS

We retrospectively analyzed adult heart transplant recipients between 2000 and 2015 extracted from the United Network for Organ Sharing registry. The whole dataset was randomly divided into a derivation set (80%) and a validation set (20%). Uni- and multivariate Cox regression were done to identify significant risk factors associated with the development of cSCC. Receiver operating charac-teristics curves were generated and area under the curve (AUC) was calculated to assess the accuracy of the prediction model. Based on the selected risk factors, a risk scoring system was developed to stratify patients into different risk groups. A cumulative cSCC-free survival curve was generated using the Kaplan-Meier method for each group, and the log-rank test was done to compare the inter-group cSCC rates.

RESULTS

There were 23736 heart-transplant recipients during the study period, and 1827 of them have been reported with cSCC. Significant predictors of post-transplant cSCC were older age, male sex, white race, recipient and donor human leukocyte antigen (HLA) mismatch level, malignancy at listing, diagnosis with restrictive myopathy or hypertrophic myopathy, heart re-transplant, and induction therapy with OKT3 or daclizumab. The multivariate model was used to predict the 5-, 8- and 10-year incidence of cSCC and respectively provided AUC of 0.79, 0.78 and 0.77 in the derivation set and 0.80, 0.78 and 0.77 in the validation set. The risk scoring system assigned each patient with a risk score within the range of 0-11, based on which they were stratified into 4 different risk groups. The predicted and observed 5-year probability of developing cSCC match well among different risk groups. In addition, the log-rank test indicated significantly different cSCC-free survival across different groups.

CONCLUSION

A risk prediction model for cSCC among heart-transplant recipients has been generated for the first time. It offers a c-statistic of ≥ 0.77 in both derivation and validation sets.

Voriconazole and the Risk of Keratinocyte Carcinomas Among Lung Transplant Recipients in the United States

Question

What is the association between voriconazole, an antifungal used to treat aspergillosis infections, and the risk of keratinocyte carcinomas among recipients of lung transplants?

Findings

In a population-based cohort study of 9599 non-Hispanic white recipients of 9793 lung transplants in the United States (2007-2016) with linkage to pharmacy claims, increasing cumulative voriconazole exposure was associated with an increased risk of cutaneous squamous cell carcinoma.

Meaning

These findings suggest that physicians caring for lung transplant recipients at high risk for aggressive keratinocyte carcinomas should limit voriconazole exposure when possible and encourage skin protection behaviors and more frequent cancer screenings.

Importance

The antifungal medication voriconazole is used to prevent and treat aspergillosis, a major cause of mortality among recipients of lung transplants (hereinafter referred to as lung recipients). Small studies suggest that voriconazole increases risk of cutaneous squamous cell carcinoma (SCC).

Objective

To examine associations of voriconazole and other antifungal medications with risk of keratinocyte carcinomas (SCC and cutaneous basal cell carcinoma [BCC]) in lung recipients.

Design, Setting, and Participants

This population-based cohort study included non-Hispanic white patients (n = 9599) who underwent lung transplant in the United States from January 1, 2007, to December 31, 2016, identified through the national Scientific Registry of Transplant Recipients with data linkable to pharmacy claims. Data were analyzed from March 1, 2018, to February 13, 2019.

Exposures

Antifungal medication use, including voriconazole, itraconazole, posaconazole, and other antifungals, was ascertained from pharmacy claims and treated as a time-varying exposure (assessed every 30 days). Cumulative antifungal exposure was calculated as the total number of exposed months.

Main Outcomes and Measures

Primary outcomes were the first SCC or BCC reported to the transplant registry by transplant centers. Follow-up began at transplant and ended at SCC or BCC diagnosis, transplant failure or retransplant, death, loss to follow-up, or December 31, 2016. Cox proportional hazards regression models were used to estimate adjusted hazard ratios (AHRs) for each antifungal medication.

Results

Among the 9793 lung transplants in 9599 recipients included in the analysis, median age at transplant was 59 (interquartile range [IQR], 48-65) years, 5824 (59.5%) were male, and 5721 (58.4%) reported ever smoking. During a median follow-up of 3.0 (IQR, 1.4-5.0) years after transplant, 1031 SCCs (incidence, 322 per 10 000 person-years) and 347 BCCs (incidence, 101 per 10 000 person-years) were reported. Compared with lung recipients with no observed voriconazole use, those with 1 to 3 months of voriconazole use experienced increased AHR for SCC of 1.09 (95% CI, 0.90-1.31); 4 to 7 months, 1.42 (95% CI, 1.16-1.73); 8 to 15 months, 2.04 (95% CI, 1.67-2.50); and more than 15 months, 3.05 (95% CI, 2.37-3.91). Ever itraconazole exposure was associated with increased SCC risk (AHR, 1.20; 95% CI, 1.00-1.45). For BCC, risk was not associated with voriconazole use but was increased with itraconazole use (AHR, 1.74; 95% CI, 1.27-2.37) or posaconazole use (AHR, 1.55; 95% CI, 1.00-2.41).

Conclusions and Relevance

In this study, voriconazole use was associated with increased SCC risk among lung recipients, especially after prolonged exposure. Further research evaluating the risk-benefit ratio of shorter courses or alternative medications in transplant recipients at high risk for SCC should be considered.

Development of Phenotyping Algorithms for the Identification of Organ Transplant Recipients: Cohort Study

Background

Studies involving organ transplant recipients (OTRs) are often limited to the variables collected in the national Scientific Registry of Transplant Recipients database. Electronic health records contain additional variables that can augment this data source if OTRs can be identified accurately.

Objective

The aim of this study was to develop phenotyping algorithms to identify OTRs from electronic health records.

Methods

We used Vanderbilt’s deidentified version of its electronic health record database, which contains nearly 3 million subjects, to develop algorithms to identify OTRs. We identified all 19,817 individuals with at least one International Classification of Diseases (ICD) or Current Procedural Terminology (CPT) code for organ transplantation. We performed a chart review on 1350 randomly selected individuals to determine the transplant status. We constructed machine learning models to calculate positive predictive values and sensitivity for combinations of codes by using classification and regression trees, random forest, and extreme gradient boosting algorithms.

Results

Of the 1350 reviewed patient charts, 827 were organ transplant recipients while 511 had no record of a transplant, and 12 were equivocal. Most patients with only 1 or 2 transplant codes did not have a transplant. The most common reasons for being labeled a nontransplant patient were the lack of data (229/511, 44.8%) or the patient being evaluated for an organ transplant (174/511, 34.1%). All 3 machine learning algorithms identified OTRs with overall >90% positive predictive value and >88% sensitivity.

Conclusions

Electronic health records linked to biobanks are increasingly used to conduct large-scale studies but have not been well-utilized in organ transplantation research. We present rigorously evaluated methods for phenotyping OTRs from electronic health records that will enable the use of the full spectrum of clinical data in transplant research. Using several different machine learning algorithms, we were able to identify transplant cases with high accuracy by using only ICD and CPT codes.

Predicting skin cancer in organ transplant recipients: development of the SUNTRAC screening tool using data from a multicenter cohort study

Skin cancer is a common post-transplant complication. In this study, the Skin and Ultraviolet Neoplasia Transplant Risk Assessment Calculator (SUNTRAC) was developed to stratify patients into risk groups for post-transplant skin cancer. Data for this study were obtained from the Transplant Skin Cancer Network (TSCN), which conducted a multicenter study across 26 transplant centers in the United States. In total, 6340 patients, transplanted from 2003 and 2008, were included. Weighted point values were assigned for each risk factor based on beta coefficients from multivariable modeling: white race (9 points), pretransplant history of skin cancer (6 points), age ≥ 50 years (4 points), male sex (2 points), and thoracic transplant (1 point). Good prognostic discrimination (optimism-corrected c statistic of 0.74) occurred with a 4-tier system: 0-6 points indicating low risk, 7-13 points indicating medium risk, 14-17 points indicating high risk, and 18-22 points indicating very high risk. The 5-year cumulative incidence of development of skin cancer was 1.01%, 6.15%, 15.14%, and 44.75%, for Low, Medium, High, and Very High SUNTRAC categories, respectively. Based on the skin cancer risk in different groups, the authors propose skin cancer screening guidelines based on this risk model.

Incidence and Risk Factors of Keratinocyte Carcinoma After First Solid Organ Transplant in Ontario, Canada

Importance

Keratinocyte carcinoma (KC), also known as nonmelanoma skin cancer, is the most common malignancy after solid organ transplant. Epidemiologic data on posttransplant KC in North America are limited by a lack of KC capture in cancer and transplant registries.

Objective

To estimate the incidence and identify risk factors for posttransplant KC.

Design, Setting, and Participants

This population-based inception cohort study in Ontario, Canada, used linked administrative databases and a health insurance claims-based algorithm. Participants were adult recipients of a first kidney, liver, heart, or lung transplant from January 1, 1994, to December 31, 2012. The cohort (n = 10 198) was followed up to December 31, 2013. Data were analyzed from May 31, 2016, to April 21, 2017.

Exposures

Solid organ transplant with functioning graft.

Main Outcomes and Measures

Age- and sex-adjusted standardized incidence ratio for KC in the transplant cohort was compared with that in the general population. Cumulative incidence of posttransplant KC was estimated using cumulative incidence functions, accounting for the competing risks of death or kidney graft loss. The association between KC and patient-, transplant-, and health services-related factors was evaluated with a multivariable cause-specific hazards model.

Results

A total of 10 198 transplant recipients were included in the study. The median (interquartile range [IQR]) age at transplant was 51 (41-59) years, with most recipients being male (6608 [64.8%]) and white (5964 [58.5%]). Posttransplant KC was diagnosed in 1690 patients (16.6%) after a median (IQR) of 3.96 (1.94-7.09) years, with an incidence rate of 2.63 per 100 patient-years (95% CI, 2.51-2.76). The rate of KC was significantly higher after transplant compared with the general population (standardized incidence ratio, 6.61; 95% CI, 6.31-6.93). The highest 10-year cumulative incidence was in the subsets of patients with a history of pretransplant skin cancer (66.5%), older than 50 years at transplant (27.5% for 51-65 years; 40.5% for >65 years), and of the white race (24.1%). The strongest independent risk factors for KC included older age at transplant (adjusted hazard ratio [aHR], 9.27; 95% CI, 7.08-12.14 for >65 years vs 18-35 years), white vs black race (aHR, 8.50; 95% CI, 4.03-17.91), pretransplant invasive skin cancer (aHR, 4.30; 95% CI, 3.72-4.98), and posttransplant precancerous skin lesions (aHR, 4.32; 95% CI, 3.77-4.95).

Conclusions and Relevance

The incidence of KC appeared to be substantially increased after transplant, particularly in patients who were older at transplant, were white, and had a history of cancerous or precancerous skin tumors; intensified skin cancer screening, education, and early use of chemopreventive interventions may be warranted for these high-risk patient subsets.

Mastomys Species as Model Systems for Infectious Diseases

Replacements of animal models by advanced in vitro systems in biomedical research, despite exceptions, are currently still not satisfactory in reproducing the whole complexity of pathophysiological mechanisms that finally lead to disease. Therefore, preclinical models are additionally required to reflect analogous in vivo situations as found in humans. Despite proven limitations of both approaches, only a combined experimental arrangement guarantees generalizability of results and their transfer to the clinics. Although the laboratory mouse still stands as a paradigm for many scientific discoveries and breakthroughs, it is mandatory to broaden our view by also using nontraditional animal models. The present review will first reflect the value of experimental systems in life science and subsequently describes the preclinical rodent model Mastomys coucha that-although still not well known in the scientific community-has a long history in research of parasites, bacteria, papillomaviruses and cancer. Using Mastomys, we could recently show for the first time that cutaneous papillomaviruses-in conjunction with UV as an environmental risk factor-induce squamous cell carcinomas of the skin via a "hit-and-run" mechanism. Moreover, Mastomys coucha was also used as a proof-of-principle model for the successful vaccination against non-melanoma skin cancer even under immunosuppressive conditions.