A prediction model for response to immune checkpoint inhibition in advanced melanoma

• Published in: International journal of cancer Vol. 154; no. 10; pp. 1760 - 1771
• Main Authors: van Duin, Isabella A J, Verheijden, Rik J, van Diest, Paul J, Blokx, Willeke A M, El-Sharouni, Mary-Ann, Verhoeff, Joost J C, Leiner, Tim, van den Eertwegh, Alfonsus J M, de Groot, Jan Willem B, van Not, Olivier J, Aarts, Maureen J B, van den Berkmortel, Franchette W P J, Blank, Christian U, Haanen, John B A G, Hospers, Geke A P, Piersma, Djura, van Rijn, Rozemarijn S, van der Veldt, Astrid A M, Vreugdenhil, Gerard, Wouters, Michel W J M, Stevense-den Boer, Marion A M, Boers-Sonderen, Marye J, Kapiteijn, Ellen, Suijkerbuijk, Karijn P M, Elias, Sjoerd G
• Format: Journal Article
• Language: English
• Published: United States Wiley Subscription Services, Inc 15.05.2024
• Subjects: Immune checkpoint inhibitors; Immunotherapy; L-Lactate dehydrogenase; Medical prognosis; Medical treatment; Melanoma; Metastases; Patients; Prediction models; Survival; melanoma; response prediction; immune checkpoint inhibition; prediction model; immunotherapy
• ISSN: 0020-7136; 1097-0215
• DOI: 10.1002/ijc.34853

Predicting who will benefit from treatment with immune checkpoint inhibition (ICI) in patients with advanced melanoma is challenging. We developed a multivariable prediction model for response to ICI, using routinely available clinical data including primary melanoma characteristics. We used a population-based cohort of 3525 patients with advanced cutaneous melanoma treated with anti-PD-1-based therapy. Our prediction model for predicting response within 6 months after ICI initiation was internally validated with bootstrap resampling. Performance evaluation included calibration, discrimination and internal-external cross-validation. Included patients received anti-PD-1 monotherapy (n = 2366) or ipilimumab plus nivolumab (n = 1159) in any treatment line. The model included serum lactate dehydrogenase, World Health Organization performance score, type and line of ICI, disease stage and time to first distant recurrence-all at start of ICI-, and location and type of primary melanoma, the presence of satellites and/or in-transit metastases at primary diagnosis and sex. The over-optimism adjusted area under the receiver operating characteristic was 0.66 (95% CI: 0.64-0.66). The range of predicted response probabilities was 7%-81%. Based on these probabilities, patients were categorized into quartiles. Compared to the lowest response quartile, patients in the highest quartile had a significantly longer median progression-free survival (20.0 vs 2.8 months; P < .001) and median overall survival (62.0 vs 8.0 months; P < .001). Our prediction model, based on routinely available clinical variables and primary melanoma characteristics, predicts response to ICI in patients with advanced melanoma and discriminates well between treated patients with a very good and very poor prognosis.