Development and Validation of a Prognostic Risk Model for Patients with Advanced Melanoma Treated with Immune Checkpoint Inhibitors.

BACKGROUND Risk stratification tools for patients with advanced melanoma (AM) treated with immune checkpoint inhibitors (ICI) are lacking. We identified a new prognostic model associated with overall survival (OS). PATIENTS AND METHODS A total of 318 treatment naïve patients with AM receiving ICI were collected from a multi-centre retrospective cohort study. LASSO Cox regression identified independent prognostic factors associated with OS. Model validation was carried out on 500 iterations of bootstrapped samples. Harrel's C-index was calculated and internally validated to outline the model's discriminatory performance. External validation was carried out in 142 advanced melanoma patients receiving ICI in later lines. RESULTS High white blood cell count (WBC), high lactate dehydrogenase (LDH), low albumin, Eastern Cooperative Oncology Group (ECOG) performance status ≥1, and the presence of liver metastases were included in the model. Patients were parsed into 3 risk groups: favorable (0-1 factors) OS of 52.9 months, intermediate (2-3 factors) OS 13.0 months, and poor (≥4 factors) OS 2.7 months. The C-index of the model from the discovery cohort was 0.69. External validation in later-lines (N = 142) of therapy demonstrated a c-index of 0.65. CONCLUSIONS Liver metastases, low albumin, high LDH, high WBC, and ECOG≥1 can be combined into a prognostic model for AM patients treated with ICI.

[1]  M. Weichenthal,et al.  Clinical Models to Define Response and Survival With Anti–PD-1 Antibodies Alone or Combined With Ipilimumab in Metastatic Melanoma , 2022, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[2]  D. Gautheret,et al.  Multi-omics prediction in melanoma immunotherapy: A new brick in the wall. , 2022, Cancer cell.

[3]  N. Bowden,et al.  Overall survival in metastatic melanoma correlates with pembrolizumab exposure and T cell exhaustion markers , 2021, Pharmacology research & perspectives.

[4]  D. Schadendorf,et al.  CheckMate 067: 6.5-year outcomes in patients (pts) with advanced melanoma. , 2021 .

[5]  Michal Sheffer,et al.  Considerations for treatment duration in responders to immune checkpoint inhibitors , 2021, Journal for ImmunoTherapy of Cancer.

[6]  T. Kirchhoff,et al.  Tumor immunogenomic signatures improve a prognostic model of melanoma survival , 2021, Journal of Translational Medicine.

[7]  Page Widick,et al.  Association of Performance Status With Survival in Patients With Advanced Non–Small Cell Lung Cancer Treated With Pembrolizumab Monotherapy , 2021, JAMA network open.

[8]  Yong Dong,et al.  The Predictive Significance of the Advanced Lung Cancer Inflammation Index (ALI) in Patients with Melanoma Treated with Immunotherapy as Second-Line Therapy , 2021, Cancer management and research.

[9]  A. Chinnaiyan,et al.  Liver metastasis restrains immunotherapy efficacy via macrophage-mediated T cell elimination , 2021, Nature Medicine.

[10]  S. Baxi,et al.  The experience of financial toxicity among advanced melanoma patients treated with immunotherapy , 2020, Journal of psychosocial oncology.

[11]  J. Bluestone,et al.  Regulatory T cell control of systemic immunity and immunotherapy response in liver metastasis , 2020, Science Immunology.

[12]  Lin Wu,et al.  Peripheral blood biomarkers associated with outcome in non-small cell lung cancer patients treated with nivolumab and durvalumab monotherapy. , 2020 .

[13]  N. Bowden,et al.  Immune checkpoint blockade in solid organ tumours: Choice, dose and predictors of response , 2020, British journal of clinical pharmacology.

[14]  P. Ascierto,et al.  The Agnostic Role of Site of Metastasis in Predicting Outcomes in Cancer Patients Treated with Immunotherapy , 2020, Vaccines.

[15]  P. Corrie,et al.  Metastatic melanoma patient outcomes since introduction of immune checkpoint inhibitors in England between 2014 and 2018 , 2020, International journal of cancer.

[16]  B. Schilling,et al.  ESMO consensus conference recommendations on the management of metastatic melanoma: under the auspices of the ESMO Guidelines Committee , 2020 .

[17]  R. Lewinson,et al.  The Lung Immune Prognostic Index Discriminates Survival Outcomes in Patients with Solid Tumors Treated with Immune Checkpoint Inhibitors , 2019, Cancers.

[18]  U. Stierner,et al.  Real-world data on PD-1 inhibitor therapy in metastatic melanoma , 2019, Acta oncologica.

[19]  S. Barni,et al.  Prognostic and predictive role of elevated lactate dehydrogenase in patients with melanoma treated with immunotherapy and BRAF inhibitors: a systematic review and meta-analysis , 2019, Melanoma research.

[20]  J. Wolchok,et al.  Five-year survival outcomes for patients with advanced melanoma treated with pembrolizumab in KEYNOTE-001 , 2019, Annals of oncology : official journal of the European Society for Medical Oncology.

[21]  S. Keam,et al.  Tissue‐specific tumor microenvironments influence responses to immunotherapies , 2019, Clinical & translational immunology.

[22]  D. Schadendorf,et al.  Five-Year Survival with Combined Nivolumab and Ipilimumab in Advanced Melanoma. , 2019, The New England journal of medicine.

[23]  J. Lunceford,et al.  Pan-tumor genomic biomarkers for PD-1 checkpoint blockade–based immunotherapy , 2018, Science.

[24]  A. Hauschild,et al.  Modeled Prognostic Subgroups for Survival and Treatment Outcomes in BRAF V600–Mutated Metastatic Melanoma: Pooled Analysis of 4 Randomized Clinical Trials , 2018, JAMA oncology.

[25]  S. Barni,et al.  Patient performance status and cancer immunotherapy efficacy: a meta-analysis , 2018, Medical Oncology.

[26]  J. Gershenwald,et al.  The eighth edition American Joint Committee on Cancer (AJCC) melanoma staging system: implications for melanoma treatment and care , 2018, Expert review of anticancer therapy.

[27]  M. Phelps,et al.  Cachectic Cancer Patients: Immune to Checkpoint Inhibitor Therapy? , 2018, Clinical Cancer Research.

[28]  J. Riess,et al.  Pembrolizumab Exposure–Response Assessments Challenged by Association of Cancer Cachexia and Catabolic Clearance , 2018, Clinical Cancer Research.

[29]  D. B. Sacdalan,et al.  Prognostic utility of baseline neutrophil-to-lymphocyte ratio in patients receiving immune checkpoint inhibitors: a review and meta-analysis , 2018, OncoTargets and therapy.

[30]  E. Jaffee,et al.  Tumor Mutational Burden and Response Rate to PD-1 Inhibition. , 2017, The New England journal of medicine.

[31]  J. Taube,et al.  Liver Metastasis and Treatment Outcome with Anti-PD-1 Monoclonal Antibody in Patients with Melanoma and NSCLC , 2017, Cancer Immunology Research.

[32]  R. Dummer,et al.  Evaluation of clinicopathological factors in PD-1 response: derivation and validation of a prediction scale for response to PD-1 monotherapy , 2017, British Journal of Cancer.

[33]  M. Atkins,et al.  Predictive biomarkers for checkpoint inhibitor-based immunotherapy. , 2016, The Lancet. Oncology.

[34]  J. Lunceford,et al.  Programmed Death-Ligand 1 Expression and Response to the Anti-Programmed Death 1 Antibody Pembrolizumab in Melanoma. , 2016, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[35]  L. Nardo,et al.  Tumor immune profiling predicts response to anti-PD-1 therapy in human melanoma. , 2016, The Journal of clinical investigation.

[36]  J. Larkin,et al.  Serum lactate dehydrogenase as an early marker for outcome in patients treated with anti-PD-1 therapy in metastatic melanoma , 2016, British Journal of Cancer.

[37]  J. Larkin,et al.  Prognostic score for patients with advanced melanoma treated with ipilimumab. , 2015, European journal of cancer.

[38]  M. Valsecchi.  Combined Nivolumab and Ipilimumab or Monotherapy in Untreated Melanoma. , 2015, The New England journal of medicine.

[39]  R. Kefford,et al.  Immune checkpoint inhibitors in melanoma. , 2015, Melanoma management.

[40]  P. Marchetti,et al.  Baseline neutrophil-to-lymphocyte ratio is associated with outcome of ipilimumab-treated metastatic melanoma patients , 2015, British Journal of Cancer.

[41]  Gary S Collins,et al.  Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD): Explanation and Elaboration , 2015, Annals of Internal Medicine.

[42]  Antoni Ribas,et al.  Anti-programmed-death-receptor-1 treatment with pembrolizumab in ipilimumab-refractory advanced melanoma: a randomised dose-comparison cohort of a phase 1 trial , 2014, The Lancet.

[43]  P. Hwu,et al.  Prognostic factors for survival in melanoma patients with brain metastases , 2011, Cancer.

[44]  G. Kaysen,et al.  POOR NUTRITIONAL STATUS AND INFLAMMATION: Serum Albumin: Relationship to Inflammation and Nutrition , 2004, Seminars in dialysis.

[45]  I. N. Crispe,et al.  Hepatic T cells and liver tolerance , 2003, Nature Reviews Immunology.

[46]  R. Motzer,et al.  Interferon-alfa as a comparative treatment for clinical trials of new therapies against advanced renal cell carcinoma. , 2002, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[47]  H. Ljunggren,et al.  Efficient presentation of exogenous antigen by liver endothelial cells to CD8+ T cells results in antigen-specific T-cell tolerance , 2000, Nature Medicine.

[48]  J. Manola,et al.  Prognostic factors in metastatic melanoma: a pooled analysis of Eastern Cooperative Oncology Group trials. , 2000, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.