Leiden University Scholarly Publications

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Duin, I.A.J. van; Verheijden, R.J.; Diest, P.J. van; Blokx, W.A.M.; El-Sharouni, M.A.; Verhoeff, J.J.C.; ... ; Elias, S.G. (2024)

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

Article / Letter to editor
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,...Show morePredicting 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.Show less
immune checkpoint inhibition
immunotherapy
melanoma
prediction model
response prediction
All authors
Duin, I.A.J. van; Verheijden, R.J.; Diest, P.J. van; Blokx, W.A.M.; El-Sharouni, M.A.; Verhoeff, J.J.C.; Leiner, T.; Eertwegh, A.J.M. van den; Groot, J.W.B. de; Not, O.J. van; Aarts, M.J.B.; Berkmortel, F.W.P.J. van den; Blank, C.U.; Haanen, J.B.A.G.; Hospers, G.A.P.; Piersma, D.; Rijn, R.S. van; Veldt, A.A.M. van der; Vreugdenhil, G.; Wouters, M.W.J.M.; Boer, M.A.M.S.D.; Boers-Sonderen, M.J.; Kapiteijn, E.; Suijkerbuijk, K.P.M.; Elias, S.G.
Date
2024-01-31
Journal
International Journal of Cancer
DOI
doi:10.1002/ijc.34853