Eastern Cooperative Oncology Group Performance Score Is Associated With Survival After Radiotherapy of Bone Metastases from Prostate Cancer

Haus, Rapha; Schild, Steven E.; Rades, Dirk

doi:10.21873/invivo.11823

Cited by 4 publications

(2 citation statements)

References 13 publications

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“…Thus, validation of the model among a sufficient number of surgically treated patients was necessary. Third, some laboratory factors [ 39 ] such as albumin, hemoglobin, and lymphocytes or the Eastern Cooperative Oncology Group score [ 40 ] were not considered for analysis in the study because of the unavailability of these data in the SEER database. Therefore, although our model obtained favorable prediction in the internal and external validation, clinical decision should not rely on survival estimation alone; it also needs a complete evaluation of the patient’s pain, neurological impairment, and general performance status.…”

Section: Discussionmentioning

confidence: 99%

A Web-Based Calculator to Predict Early Death Among Patients With Bone Metastasis Using Machine Learning Techniques: Development and Validation Study

Lei,

Wu,

Zhang

et al. 2023

J Med Internet Res

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Background Patients with bone metastasis often experience a significantly limited survival time, and a life expectancy of <3 months is generally regarded as a contraindication for extensive invasive surgeries. In this context, the accurate prediction of survival becomes very important since it serves as a crucial guide in making clinical decisions. Objective This study aimed to develop a machine learning–based web calculator that can provide an accurate assessment of the likelihood of early death among patients with bone metastasis. Methods This study analyzed a large cohort of 118,227 patients diagnosed with bone metastasis between 2010 and 2019 using the data obtained from a national cancer database. The entire cohort of patients was randomly split 9:1 into a training group (n=106,492) and a validation group (n=11,735). Six approaches—logistic regression, extreme gradient boosting machine, decision tree, random forest, neural network, and gradient boosting machine—were implemented in this study. The performance of these approaches was evaluated using 11 measures, and each approach was ranked based on its performance in each measure. Patients (n=332) from a teaching hospital were used as the external validation group, and external validation was performed using the optimal model. Results In the entire cohort, a substantial proportion of patients (43,305/118,227, 36.63%) experienced early death. Among the different approaches evaluated, the gradient boosting machine exhibited the highest score of prediction performance (54 points), followed by the neural network (52 points) and extreme gradient boosting machine (50 points). The gradient boosting machine demonstrated a favorable discrimination ability, with an area under the curve of 0.858 (95% CI 0.851-0.865). In addition, the calibration slope was 1.02, and the intercept-in-large value was −0.02, indicating good calibration of the model. Patients were divided into 2 risk groups using a threshold of 37% based on the gradient boosting machine. Patients in the high-risk group (3105/4315, 71.96%) were found to be 4.5 times more likely to experience early death compared with those in the low-risk group (1159/7420, 15.62%). External validation of the model demonstrated a high area under the curve of 0.847 (95% CI 0.798-0.895), indicating its robust performance. The model developed by the gradient boosting machine has been deployed on the internet as a calculator. Conclusions This study develops a machine learning–based calculator to assess the probability of early death among patients with bone metastasis. The calculator has the potential to guide clinical decision-making and improve the care of patients with bone metastasis by identifying those at a higher risk of early death.

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Section: Discussionmentioning

confidence: 99%

A Web-Based Calculator to Predict Early Death Among Patients With Bone Metastasis Using Machine Learning Techniques: Development and Validation Study

Lei,

Wu,

Zhang

et al. 2023

J Med Internet Res

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“…The ECOG performance status is an assessment of the patients' functional status (41). A better ECOG performance status is associated with better clinical outcomes in cancer patients, irrespective of the type of systemic therapy (42,43). All the five studies enrolled in the analysis of ORR of anti-PD-1/anti-PD-L1 therapy according to the ECOG performance status showed a higher ORR in patients with a score of zero than those with a score of one.…”

Section: Discussionmentioning

confidence: 99%

Predictors for the clinical benefit of anti-PD-1/PD-L1 therapy in advanced gastroesophageal cancer: a meta-analysis of clinical trials

et al. 2020

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Background: The overall objective response rate (ORR) of published clinical trials in advanced gastroesophageal cancer patients who received anti-program-death-1 (anti-PD-1) or program-deathlegend-1 (anti-PD-L1) therapy was only 10%. This ratio is far away from satisfying. It is necessary to identify patients who are more likely to benefit from the treatment. This study aimed to identify the factors with which the patients would have a higher response rate to anti-PD-1/anti-PD-L1 therapy.Methods: The study was carried out according to the Cochrane handbook for systemic reviews of intervention. The comparisons were conducted according to the patients' characteristics to distinguish the factors with which the patients would have a higher response rate and better survival from the therapy.Results: One thousand and nine hundred ninety-eight patients with advanced gastroesophageal cancer receiving anti-PD-1 or anti-PD-L-1 therapy were enrolled totally. Both the anti-PD-1 and anti-PD-L-1 therapy were significantly more efficacy in patients with high expression of PD-L1. Adenocarcinoma patients with high microsatellite instability (MSI-H) were more likely to benefit from anti-PD-1 therapy. Patients with a better Eastern Cooperative Oncology Group (ECOG) performance status had a significantly higher ORR and disease control rate (DCR). The treatment also had a better performance in improving the overall survival (OS) and progression-free survival (PFS) in patients with high expression of PD-L1.

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Association of dynamic change in patient-reported pain with survival in metastatic castrate sensitive prostate cancer—exploratory analysis of LATITUDE study

Roy

Morgan

Wallis

et al. 2022

Prostate Cancer Prostatic Dis

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Eastern Cooperative Oncology Group Performance Score Is Associated With Survival After Radiotherapy of Bone Metastases from Prostate Cancer

Cited by 4 publications

References 13 publications

A Web-Based Calculator to Predict Early Death Among Patients With Bone Metastasis Using Machine Learning Techniques: Development and Validation Study

A Web-Based Calculator to Predict Early Death Among Patients With Bone Metastasis Using Machine Learning Techniques: Development and Validation Study

Predictors for the clinical benefit of anti-PD-1/PD-L1 therapy in advanced gastroesophageal cancer: a meta-analysis of clinical trials

Association of dynamic change in patient-reported pain with survival in metastatic castrate sensitive prostate cancer—exploratory analysis of LATITUDE study

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