A practical prognostic peripheral blood-based risk model for the evaluation of the likelihood of a response and survival of metastatic cancer patients treated with immune checkpoint inhibitors

Q: Which pretreatment factors were used to build the risk model?

The model used six inflammation-related laboratory parameters—neutrophils, platelets, CRP, ESR, LDH, and anemia—scored to produce 0–6 risk points.

Q: How did the risk groups perform in treatment outcomes?

The high-risk group showed a lower overall response rate than the low-risk group, and it also had shorter overall survival and progression-free survival, with risk remaining significant in multivariate Cox analyses.

Sep 24, 2026

Uploaded by Bulrr

Background: Less than half of unselected metastatic cancer patients benefit from immune checkpoint inhibitor (ICI) therapy. Systemic inflammation may affect ICI efficacy, making routine inflammatory laboratory markers valuable for prognosis and/or prediction. This study aimed to identify an inflammation-related parameter combination to build a practical pretreatment risk model for response and survival in ICI-treated patients across metastatic cancer types. Methods: Inflammation markers and anemia were scored to stratify risk groups and evaluate ORR, OS, and PFS.

LanguageEnglish

CategoryHealthcare

FormatPDF

Pages11

Reading Time28 min

AccessFree to download

Abstract

Background

Methods

Results

Conclusions

Keywords

Background

Biomarkers for ICI response

Tiainen etal. BMC Cancer (2023) 23:1186 BMC Cancer [https://doi.org/10.1186/s12885-023-11699-0](https://doi.org/10.1186/s12885-023-11699-0) RESEARCH Open Access A practical prognostic peripheral blood-based risk model for the evaluation of the likelihood of a response and survival of metastatic cancer patients treated with immune checkpoint inhibitors Satu Tiainen1,2, Veera Nurmela2, Tuomas Selander3, Patrik Turunen2, Sanna Pasonen-Seppänen4, Tiia Kettunen 1,2, Outi Kuittinen 1,2, Päivi Auvinen1,2 and Aino Rönkä1,2* Abstract Background Less than half of unselected metastatic cancer patients benefit from the immune checkpoint inhibitor (ICI) therapy. Systemic cancer-related inflammation may influence the efficacy of ICIs and thus, systemic inflammatory markers could have prognostic and/or predictive potential in ICI therapy. Here, we aimed to identify a combination of inflammation-related laboratory parameters to establish a practical prognostic risk model for the pretreatment evaluation of a response and survival of ICI-treated patients with different types of metastatic cancers. Methods The study-cohort consisted of a real-world patient population receiving ICIs for metastatic cancers of different origins (n = 158) . Laboratory parameters determined before the initiation of the ICI treatment were retrospectively collected. Six inflammation-related parameters i. e., elevated values of neutrophils, platelets, C-reactive protein (CRP), erythrocyte sedimentation rate (ESR) and lactate dehydrogenase (LDH), and the presence of anemia, were each scored with one point, giving 0–6 risk points for each patient. The patients with information of all these six parameters (n = 109) were then stratified into low-risk (0–3 points) and high-risk (4–6 points) groups. The overall response rate (ORR), overall survival (OS), and progression-free survival (PFS) according to the risk scores were determined. Results The risk model was strongly associated with the outcome of the patients. The ORR to ICI treatment in the high-risk group was 30 . 3% in comparison to 53 . 9% in the low-risk group (p = 0 . 023) . The medians for OS were 10.0 months and 27.3 months, respectively (p < 0. 001), and the corresponding medians for PFS were 3.9 months and 6.3 months (p = 0 . 002) . The risk group remained as a significant prognostic factor for both OS (HR 3 . 04, 95% CI 1.64–5. 64, p < 0. 001) and PFS (HR 1. 79, 95% CI 1.04–3. 06, p = 0 . 035) in the Cox multivariate analyses. *Correspondence: Aino Rönkä [aino. ronka@pshyvinvointialue.fi](aino. ronka@pshyvinvointialue.fi) Full list of author information is available at the end of the article © The Author(s) 2023. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit [http://creativecommons.org/licenses/by/4.0/](http://creativecommons.org/licenses/by/4.0/. The)[. The](http://creativecommons.org/licenses/by/4.0/. The)[ ](http://creativecommons.org/licenses/by/4.0/. The)Creative Commons Public Domain Dedication waiver ([http://creativecommons.org/publicdomain/zero/1.0/](http://creativecommons.org/publicdomain/zero/1.0/)) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Tiainen et al. BMC Canc

FAQs

What problem does this study address for immune checkpoint inhibitor therapy?

Less than half of unselected metastatic cancer patients benefit from ICI therapy, so the study focuses on identifying pretreatment measures that can better estimate response and survival.

Which pretreatment factors were used to build the risk model?

The model used six inflammation-related laboratory parameters—neutrophils, platelets, CRP, ESR, LDH, and anemia—scored to produce 0–6 risk points.

How did the risk groups perform in treatment outcomes?

The high-risk group showed a lower overall response rate than the low-risk group, and it also had shorter overall survival and progression-free survival, with risk remaining significant in multivariate Cox analyses.

Sep 24, 2026

Uploaded by Bulrr