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Key Prognostic Factors Create a Composite Risk Score to Stratify Patients into High- and Low-Treatment Benefit Groups: A Multicenter, Retrospective Data Analysis of 84 Metastatic Colorectal Cancer Patients Treated with Regorafenib as Part of the CORRECT and CONSIGN Trials
INTRODUCTION: In further-line mCRC treatment, median progression-free survival (PFS) is rather short, and many patients do not benefit from any antitumor treatment and should therefore be treated according to best-supportive care. A risk score based on standard laboratory values using markers of tum...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
S. Karger AG
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10614442/ https://www.ncbi.nlm.nih.gov/pubmed/37607525 http://dx.doi.org/10.1159/000531268 |
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author | Zöhrlaut, Linda Katharina Karthaus, Meinolf Vehling-Kaiser, Ursula von Kunhardt, Lukas Stintzing, Sebastian Heinemann, Volker von Einem, Jobst C. |
author_facet | Zöhrlaut, Linda Katharina Karthaus, Meinolf Vehling-Kaiser, Ursula von Kunhardt, Lukas Stintzing, Sebastian Heinemann, Volker von Einem, Jobst C. |
author_sort | Zöhrlaut, Linda Katharina |
collection | PubMed |
description | INTRODUCTION: In further-line mCRC treatment, median progression-free survival (PFS) is rather short, and many patients do not benefit from any antitumor treatment and should therefore be treated according to best-supportive care. A risk score based on standard laboratory values using markers of tumor inflammation aims to define a patient cohort with high treatment benefit and might offer insights into tumor biology. As regorafenib has been dropped off the German market due to an unfavorable risk-benefit ratio, patient selection is key for any further-line treatment option. METHODS: We used Cox regression analysis to determine laboratory markers that are independent prognostic factors of OS and PFS outcome. The influence of these variables was weighted using an estimator, which was calculated using Cox regression analysis. The estimators were implemented as multiplication factors, resulting in a risk score. A cut-off value for the resulting risk values was then determined via Cox regression analysis resulting in a low- and high-risk subgroup. RESULTS: Using data of 82 patients, a risk score identifying long-term survival in patients with last-line mCRC treatment could be calculated. The following parameters were associated with significantly longer survival in multivariate analysis: NLR ≤5 (p = <0.001), AP ≤200 U/L (p = 0.001), CRP ≤3.2 mg/dL (p = <0.001). The following estimator values were used to calculate a risk score: NLR: 0.132 (p = 0.046), AP: 0.004 (p = 0.014), and CRP: 0.032 (p = 0.039). Implementing the estimators as multiplication factors yielded the following risk score: 0.132*NLR + 0.004*AP + 0.032*CRP = Risk value. Cox regression resulted in low- and high-risk subgroups with risk values below and above 1.4, respectively. In the group with a low-risk score (<1.4), patients had a median OS of 10.5 months after initiating regorafenib. Patients with a high-risk score (>1.4) survived only 3.3 months after starting therapy with regorafenib (n = 43, p < 0.001, HR = 3.76). CONCLUSIONS: The presented composite risk score stratifies patients into two prognostic subgroups characterized by standard laboratory values. Patients with signs of systemic inflammation characterized by elevated NLR, AP, and CRP have a high composite risk score and a significant shorter overall survival. Although this score needs to be prospectively validated in larger cohorts, it may be used to stratify patients suitable for further-line treatment studies. |
format | Online Article Text |
id | pubmed-10614442 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | S. Karger AG |
record_format | MEDLINE/PubMed |
spelling | pubmed-106144422023-10-31 Key Prognostic Factors Create a Composite Risk Score to Stratify Patients into High- and Low-Treatment Benefit Groups: A Multicenter, Retrospective Data Analysis of 84 Metastatic Colorectal Cancer Patients Treated with Regorafenib as Part of the CORRECT and CONSIGN Trials Zöhrlaut, Linda Katharina Karthaus, Meinolf Vehling-Kaiser, Ursula von Kunhardt, Lukas Stintzing, Sebastian Heinemann, Volker von Einem, Jobst C. Oncol Res Treat Research Article INTRODUCTION: In further-line mCRC treatment, median progression-free survival (PFS) is rather short, and many patients do not benefit from any antitumor treatment and should therefore be treated according to best-supportive care. A risk score based on standard laboratory values using markers of tumor inflammation aims to define a patient cohort with high treatment benefit and might offer insights into tumor biology. As regorafenib has been dropped off the German market due to an unfavorable risk-benefit ratio, patient selection is key for any further-line treatment option. METHODS: We used Cox regression analysis to determine laboratory markers that are independent prognostic factors of OS and PFS outcome. The influence of these variables was weighted using an estimator, which was calculated using Cox regression analysis. The estimators were implemented as multiplication factors, resulting in a risk score. A cut-off value for the resulting risk values was then determined via Cox regression analysis resulting in a low- and high-risk subgroup. RESULTS: Using data of 82 patients, a risk score identifying long-term survival in patients with last-line mCRC treatment could be calculated. The following parameters were associated with significantly longer survival in multivariate analysis: NLR ≤5 (p = <0.001), AP ≤200 U/L (p = 0.001), CRP ≤3.2 mg/dL (p = <0.001). The following estimator values were used to calculate a risk score: NLR: 0.132 (p = 0.046), AP: 0.004 (p = 0.014), and CRP: 0.032 (p = 0.039). Implementing the estimators as multiplication factors yielded the following risk score: 0.132*NLR + 0.004*AP + 0.032*CRP = Risk value. Cox regression resulted in low- and high-risk subgroups with risk values below and above 1.4, respectively. In the group with a low-risk score (<1.4), patients had a median OS of 10.5 months after initiating regorafenib. Patients with a high-risk score (>1.4) survived only 3.3 months after starting therapy with regorafenib (n = 43, p < 0.001, HR = 3.76). CONCLUSIONS: The presented composite risk score stratifies patients into two prognostic subgroups characterized by standard laboratory values. Patients with signs of systemic inflammation characterized by elevated NLR, AP, and CRP have a high composite risk score and a significant shorter overall survival. Although this score needs to be prospectively validated in larger cohorts, it may be used to stratify patients suitable for further-line treatment studies. S. Karger AG 2023-08-22 2023-09 /pmc/articles/PMC10614442/ /pubmed/37607525 http://dx.doi.org/10.1159/000531268 Text en © 2023 The Author(s). Published by S. Karger AG, Basel https://creativecommons.org/licenses/by-nc/4.0/This article is licensed under the Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC) (http://www.karger.com/Services/OpenAccessLicense). Usage and distribution for commercial purposes requires written permission. |
spellingShingle | Research Article Zöhrlaut, Linda Katharina Karthaus, Meinolf Vehling-Kaiser, Ursula von Kunhardt, Lukas Stintzing, Sebastian Heinemann, Volker von Einem, Jobst C. Key Prognostic Factors Create a Composite Risk Score to Stratify Patients into High- and Low-Treatment Benefit Groups: A Multicenter, Retrospective Data Analysis of 84 Metastatic Colorectal Cancer Patients Treated with Regorafenib as Part of the CORRECT and CONSIGN Trials |
title | Key Prognostic Factors Create a Composite Risk Score to Stratify Patients into High- and Low-Treatment Benefit Groups: A Multicenter, Retrospective Data Analysis of 84 Metastatic Colorectal Cancer Patients Treated with Regorafenib as Part of the CORRECT and CONSIGN Trials |
title_full | Key Prognostic Factors Create a Composite Risk Score to Stratify Patients into High- and Low-Treatment Benefit Groups: A Multicenter, Retrospective Data Analysis of 84 Metastatic Colorectal Cancer Patients Treated with Regorafenib as Part of the CORRECT and CONSIGN Trials |
title_fullStr | Key Prognostic Factors Create a Composite Risk Score to Stratify Patients into High- and Low-Treatment Benefit Groups: A Multicenter, Retrospective Data Analysis of 84 Metastatic Colorectal Cancer Patients Treated with Regorafenib as Part of the CORRECT and CONSIGN Trials |
title_full_unstemmed | Key Prognostic Factors Create a Composite Risk Score to Stratify Patients into High- and Low-Treatment Benefit Groups: A Multicenter, Retrospective Data Analysis of 84 Metastatic Colorectal Cancer Patients Treated with Regorafenib as Part of the CORRECT and CONSIGN Trials |
title_short | Key Prognostic Factors Create a Composite Risk Score to Stratify Patients into High- and Low-Treatment Benefit Groups: A Multicenter, Retrospective Data Analysis of 84 Metastatic Colorectal Cancer Patients Treated with Regorafenib as Part of the CORRECT and CONSIGN Trials |
title_sort | key prognostic factors create a composite risk score to stratify patients into high- and low-treatment benefit groups: a multicenter, retrospective data analysis of 84 metastatic colorectal cancer patients treated with regorafenib as part of the correct and consign trials |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10614442/ https://www.ncbi.nlm.nih.gov/pubmed/37607525 http://dx.doi.org/10.1159/000531268 |
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