Disparity in outcomes of melanoma adjuvant immunotherapy by demographic profile

Effects of treatment methods on cutaneous melanoma related mortality and all-cause mortality in Texas: TCR-Medicare 2007-2017 database

PURPOSE

The incidence of cutaneous melanoma is rising, and Melanoma related deaths are highest among people aged 65-74. Herein, we aim to understand the impact of novel and established melanoma treatment methods on CM related mortality and all-cause mortality. We further compared these effects among Hispanic and non-Hispanic Whites (NHW).

METHODS

The data was extracted from the Texas Cancer Registry from 2007 to 2017. A Cox Proportional Hazard regression analysis was performed to assess treatment effect on melanoma mortality and all-cause mortality, with race-ethnicity as an effect modifier.

RESULTS

A higher percentage of Hispanic patients presented with CM-related mortality (22.11%) compared to NHW patients (14.39%). In both the Hispanic and NHW, post-diagnosis radiation (HR = 1.610, 95% CI 0.984-2.634, HR = 2.348, 95% CI 2.082-2.648, respectively), post-diagnosis chemotherapy (HR = 1.899, 95% CI 1.085-3.322, HR = 2.035, 95% CI 1.664-2.489, respectively), and post-diagnosis immunotherapy (HR = 2.100, 95% CI 1.338-3.296, HR = 2.402, 95% CI 2.100-2.748) are each associated with an increased risk in CM-related mortality. Similar results were seen with post-diagnosis radiation (Hispanic HR = 1.640, 95% CI 1.121-2.400, NHW HR = 1.800, 95% CI 1.644-1.971), post-diagnostic chemotherapy (Hispanic HR = 1.457, 95% CI 0.898-2.364, NHW HR = 1.592, 95% CI 1.356-1.869), and post-diagnosis immunotherapy (Hispanic HR = 2.140, 95% CI 1.494-3.065, NHW HR = 2.190, 95% CI 1.969-2.435) with respect to all-cause mortality. Post-diagnosis surgery (HR = 0.581, 95% CI 0.395-0.856, HR = 0.622, 95% CI 0.571-0.678) had the opposite effect in CM-related mortality for Hispanics and NHWs respectively.

CONCLUSION

Our results propose differences in all-cause and CM-only related mortality with separate treatment modalities, particularly with chemotherapy, radiation therapy and immunotherapy. In addition, this retrospective cohort study showed that health disparities exist in the Hispanic Medicare population of Texas with CM.

Disparity in initiation of checkpoint inhibitors among commercially insured and Medicare Advantage patients with metastatic melanoma

BACKGROUND: Immune checkpoint inhibitors (ICIs) have revolutionized the treatment of advanced melanoma, but racial disparities in melanoma outcomes continue. These inequities are not fully explained by individual factors. OBJECTIVE: To investigate the associations of neighborhood factors with the use of ICIs in metastatic melanoma. METHODS: We conducted a retrospective cohort study of commercially insured US adults with metastatic melanoma diagnosed between January 2011 and December 2020. We examined the associations between the county-level percentage of population from racial and ethnic minority groups and the time from metastatic melanoma diagnosis to initiating ICIs using Cox proportional hazards models adjusting for patient characteristics. RESULTS: We identified 4,052 patients with metastatic melanoma, of which 49% used ICIs. We found that the adoption of ICIs in a county declined with increasing minority quintile (quintile 1: 52.4%, quintile 2: 50.4%, quintile 3: 50.1%, quintile 4: 45.8%, and quintile 5: 44.7%). The delay in ICI initiation also went up as the percentage of minorities in a county increased (log-rank test P = 0.03). Compared with the lowest quintile, the adjusted hazard ratio of ICI initiation of the second, third, fourth, and highest minority quintile was 0.94 (95% CI = 0.81-1.08), 0.88 (95% CI = 0.76-1.02), 0.81 (95% CI = 0.68-0.97), and 0.77 (95% CI = 0.66-0.91), respectively. Secondary analysis revealed that the slower initiation was driven by the counties with the highest percentage of Hispanic population (hazard ratio = 0.74; 95% CI = 0.61-0.89) in both Cox models and sensitivity analyses. High-minority counties correlated with metro areas, higher poverty levels, and a greater number of medical oncologists. CONCLUSIONS: We found that patients with metastatic melanoma living in counties with higher proportion of minorities, particularly of Hispanic origin, are more likely to experience delays in ICI treatment. This study provides important population-level data on neighborhood-level disparity in medication use. More research is needed on the underlying provider- and system-level factors that directly contributed to the lower use of cancer medicines in high-minority areas, which can help inform the development of evidence-based medication use strategies that can improve health outcomes and equity.

Machine learning for prediction of immunotherapeutic outcome in non-small-cell lung cancer based on circulating cytokine signatures

BACKGROUND

Immune checkpoint inhibitor (ICI) therapy has substantially improved the overall survival (OS) in patients with non-small-cell lung cancer (NSCLC); however, its response rate is still modest. In this study, we developed a machine learning-based platform, namely the Cytokine-based ICI Response Index (CIRI), to predict the ICI response of patients with NSCLC based on the peripheral blood cytokine profiles.

METHODS

We enrolled 123 and 99 patients with NSCLC who received anti-PD-1/PD-L1 monotherapy or combined chemotherapy in the training and validation cohorts, respectively. The plasma concentrations of 93 cytokines were examined in the peripheral blood obtained from patients at baseline (pre) and 6 weeks after treatment (early during treatment: edt). Ensemble learning random survival forest classifiers were developed to select feature cytokines and predict the OS of patients undergoing ICI therapy.

RESULTS

Fourteen and 19 cytokines at baseline and on treatment, respectively, were selected to generate CIRI models (namely preCIRI14 and edtCIRI19), both of which successfully identified patients with worse OS in two completely independent cohorts. At the population level, the prediction accuracies of preCIRI14 and edtCIRI19, as indicated by the concordance indices (C-indices), were 0.700 and 0.751 in the validation cohort, respectively. At the individual level, patients with higher CIRI scores demonstrated worse OS [hazard ratio (HR): 0.274 and 0.163, and p<0.0001 and p=0.0044 in preCIRI14 and edtCIRI19, respectively]. By including other circulating and clinical features, improved prediction efficacy was observed in advanced models (preCIRI21 and edtCIRI27). The C-indices in the validation cohort were 0.764 and 0.757, respectively, whereas the HRs of preCIRI21 and edtCIRI27 were 0.141 (p<0.0001) and 0.158 (p=0.038), respectively.

CONCLUSIONS

The CIRI model is highly accurate and reproducible in determining the patients with NSCLC who would benefit from anti-PD-1/PD-L1 therapy with prolonged OS and may aid in clinical decision-making before and/or at the early stage of treatment.

Improved prediction of immune checkpoint blockade efficacy across multiple cancer types

Only a fraction of patients with cancer respond to immune checkpoint blockade (ICB) treatment, but current decision-making procedures have limited accuracy. In this study, we developed a machine learning model to predict ICB response by integrating genomic, molecular, demographic and clinical data from a comprehensively curated cohort (MSK-IMPACT) with 1,479 patients treated with ICB across 16 different cancer types. In a retrospective analysis, the model achieved high sensitivity and specificity in predicting clinical response to immunotherapy and predicted both overall survival and progression-free survival in the test data across different cancer types. Our model significantly outperformed predictions based on tumor mutational burden, which was recently approved by the U.S. Food and Drug Administration for this purpose¹. Additionally, the model provides quantitative assessments of the model features that are most salient for the predictions. We anticipate that this approach will substantially improve clinical decision-making in immunotherapy and inform future interventions.

Treatment of Metastatic Melanoma in the Elderly

PURPOSE OF REVIEW

This study aims to review the clinical experience of melanoma treatments in patients with advanced age.

RECENT FINDINGS

During the last decade, the treatment paradigm for melanoma has changed dramatically with the use of checkpoint inhibitors, oncolytic viruses, and targeted therapies. We reviewed both the clinical trial and real-world experience of these therapies in patients of advanced age, and discuss how a personalized approach should be taken for these patients with consideration of incidence and management of side effects. Although special consideration should be taken, immunotherapy, oncolytic viruses, and targeted therapy have shown efficacy and tolerability in older patients with melanoma.

Thyroid-related adverse events induced by immune checkpoint inhibitors

Immune checkpoint inhibitors, namely anti-CTLA-4, anti-PD-1 and anti-PD-L1 monoclonal antibodies, have emerged in the last decade as a novel form of cancer treatment, promoting increased survival in patients. As they tamper with the immune response in order to destroy malignant cells, a new type of adverse reactions has emerged, known as immune-related adverse events (irAEs), which frequently target the endocrine system, especially the thyroid and hypophysis. Thyroid irAEs include hyperthyroidism, thyrotoxicosis, hypothyroidism and a possibly life-threatening condition known as the "thyroid storm". Early prediction of occurrence and detection of the thyroid irAEs should be a priority for the clinician, in order to avoid critical situations. Moreover, they are recently considered both a prognostic marker and a means of overseeing treatment response, since they indicate an efficient activation of the immune system. Therefore, a multidisciplinary approach including both oncologists and endocrinologists is recommended when immune checkpoint inhibitors are used in the clinic.