ArticleCancer medicine2016
The full blood count as a biomarker of outcome and toxicity in ipilimumab-treated cutaneous metastatic melanoma.
Article in Cancer medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers, 8 of them syntheses that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
47 citing papers in PubMed, 8 syntheses or guidelines pooled it, 86 citations in OpenAlex.
- Predictive value of serum biomarkers for survival in melanoma: a systematic review and meta-analysis.Scientific reports · 2026Pooled it
- Baseline risk factors associated with immune related adverse events and atezolizumab.Frontiers in oncology · 2023Pooled it
- Prognostic role of the platelet to lymphocyte ratio (PLR) in the clinical outcomes of patients with advanced lung cancer receiving immunotherapy: A systematic review and meta-analysis.Frontiers in oncology · 2022Pooled it
- Prognostic significance of platelet lymphocyte ratio in patients with melanoma: A meta-analysis.Medicine · 2021Pooled it
- Prognostic and clinicopathological significance of the platelet-to-lymphocyte ratio in melanoma: A meta-analysis involving 2099 patients.The Kaohsiung journal of medical sciences · 2021Pooled it
- Prognostic Value of the Platelet-to-Lymphocyte Ratio in Patients With Melanoma: A Meta-Analysis.Frontiers in oncology · 2020Pooled it
- Biomarkers, measured during therapy, for response of melanoma patients to immune checkpoint inhibitors: a systematic review.Melanoma research · 2019Pooled it
- Pretreatment hematological markers predict clinical outcome in cancer patients receiving immune checkpoint inhibitors: A meta-analysis.Thoracic cancer · 2018Pooled it
- Low-dose interferon-alpha preconditioning and adoptive cell therapy in patients with metastatic melanoma refractory to standard (immune) therapies: a phase I/II study.Journal for immunotherapy of cancer · 2020Trial
- Prognostic biomarkers for immunotherapy with ipilimumab in metastatic melanoma.Clinical and experimental immunology · 2019Trial
- A composite score of serum cytokines enables early identification of patients at high risk for irAEs under immune checkpoint inhibition.Frontiers in immunology · 2025Article
- Prognostic Potential of Baseline Eosinophils at the Initiation of Immune Checkpoint Inhibitor Treatment of Metastatic Melanoma: A Systematic Review and Meta-Analysis.Journal of skin cancer · 2025Review
- Non-Invasive Predictive Biomarkers for Immune-Related Adverse Events Due to Immune Checkpoint Inhibitors.Cancers · 2024Review
- Eosinophilic granulocytes as a potential prognostic marker for cancer progression and therapeutic response in malignant melanoma.Frontiers in oncology · 2024Review
- Immune checkpoint inhibitor-related pneumonitis: research advances in prediction and management.Frontiers in immunology · 2024Review
- Biomarkers and risk factors for the early prediction of immune-related adverse events: a review.Human vaccines & immunotherapeutics · 2022Review
- CD21Journal of personalized medicine · 2022Article
- External validation of biomarkers for immune-related adverse events after immune checkpoint inhibition.Frontiers in immunology · 2022Article
- Correlations between peripheral blood biomarkers and clinical outcomes in advanced non-small cell lung cancer patients who received immunotherapy-based treatments.Translational lung cancer research · 2021Article
- Does the Use of Peripheral Immune-Related Markers Indicate Whether to Administer Pazopanib, Trabectedin, or Eribulin to Advanced Soft Tissue Sarcoma Patients?Journal of clinical medicine · 2021Article
Corrections and comments
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Authors and funding
9 authors at 3 institutions in 3 countries.
Funding
Abstract
Ipilimumab produces durable responses in some metastatic melanoma patients. Neutrophil, platelet, and eosinophil to lymphocyte ratios (NLR, PLR, and ELR) may be associated with the immune response in cancer thereby acting as biomarkers of toxicity and efficacy in ipilimumab-treated patients. Data were collected on clinical characteristics and lactate dehydrogenase (LDH), NLR, PLR, and ELR at baseline, post cycle 2 and at the end of treatment for 183 patients treated with ipilimumab between 2008 and 2015 at the Princess Margaret Cancer Centre. Associations between clinical characteristics, LDH, NLR, PLR, and ELR with toxicity or survival outcomes of progression-free (PFS) and overall survival (OS) were assessed using univariable and multivariable analysis. Prognostic models of outcome at each time point were determined. Of the 183 patients included, the median age was 58, 85% had M1c disease, 58% were performance status 1, and 64% received ipilimumab as second line therapy. Median follow up was 7.5 months (range: 0.3-49.5), median PFS was 2.8 months (95% confidence intervals (CI): 2.8-3.2), and median OS was 9.6 months (95% CI: 7.9-13.2). Prognostic factors for OS by multivariable analysis were LDH and NLR at all-time points. Prognostic models using LDH (× 2 upper limit of normal) and NLR 4) differentiated patients into high, moderate, and low risk of death prior to or on ipilimumab treatment (P < 0.0001 for each model). No factors were associated with toxicity. Prognostic models based on NLR and LDH values at baseline and on treatment differentiate patients into good, intermediate, and poor prognostic groups and may be relevant in patient management.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.