Background: Few prognostic models for overall survival (OS) are available for patients with metastatic castration-resistant prostate cancer (mCRPC) treated with recently approved agents. We developed a prognostic index model using readily available clinical and laboratory factors from a phase III trial of abiraterone acetate (hereafter abiraterone) in combination with prednisone in post-docetaxel mCRPC.
Patients And Methods: Baseline data were available from 762 patients treated with abiraterone-prednisone. Factors were assessed for association with OS through a univariate Cox model and used in a multivariate Cox model with a stepwise procedure to identify those of significance. Data were validated using an independent, external, population-based cohort.
Results: Six risk factors individually associated with poor prognosis were included in the final model: lactate dehydrogenase > upper limit of normal (ULN) [hazard ratio (HR) = 2.31], Eastern Cooperative Oncology Group performance status of 2 (HR = 2.19), presence of liver metastases (HR = 2.00), albumin ≤4 g/dl (HR = 1.54), alkaline phosphatase > ULN (HR = 1.38) and time from start of initial androgen-deprivation therapy to start of treatment ≤36 months (HR = 1.30). Patients were categorized into good (n = 369, 46%), intermediate (n = 321, 40%) and poor (n = 107, 13%) prognosis groups based on the number of risk factors and relative HRs. The C-index was 0.70 ± 0.014. The model was validated by the external dataset (n = 286).
Conclusion: This analysis identified six factors used to model survival in mCRPC and categorized patients into three distinct risk groups. Prognostic stratification with this model could assist clinical practice decisions for follow-up and monitoring, and may aid in clinical trial design.
Trial Registration Numbers: NCT00638690.
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http://dx.doi.org/10.1093/annonc/mdv594 | DOI Listing |
Biol Direct
January 2025
School of Medicine, South China University of Technology, Guangzhou, 510006, China.
Background: Pancreatic cancer is characterized by a complex tumor microenvironment that hinders effective immunotherapy. Identifying key factors that regulate the immunosuppressive landscape is crucial for improving treatment strategies.
Methods: We constructed a prognostic and risk assessment model for pancreatic cancer using 101 machine learning algorithms, identifying OSBPL3 as a key gene associated with disease progression and prognosis.
BMC Cancer
January 2025
Department of Hepatobiliary Surgery, Guangxi Medical University Cancer Hospital, Nanning, Guangxi Province, 530021, China.
Background And Objective: In clinical practice, CK19 can be an important predictor for the prognosis of HCC. Due to the high incidence and mortality rates of HCC, more effective and practical prognostic prediction models need to be developed urgently.
Methods: A total of 1,168 HCC patients, who underwent radical surgery at the Guangxi Medical University Cancer Hospital, between January 2014 and July 2019, were recruited, and their clinicopathological data were collected.
Discov Oncol
January 2025
Shandong University School of Medicine, 44 Wenhua Xi Road, Jinan, 250012, Shandong, China.
Introduction: With the increasing impact of hepatocellular carcinoma (HCC) on society, there is an urgent need to propose new HCC diagnostic biomarkers and identification models. Histone lysine lactylation (Kla) affects the prognosis of cancer patients and is an emerging target in cancer treatment. However, the potential of Kla-related genes in HCC is poorly understood.
View Article and Find Full Text PDFJ Cell Mol Med
January 2025
Department of Andrology, The First Hospital of Jilin University, Changchun, China.
Prostate cancer (PCa) is one of the most common cancers in men worldwide. Autophagy-related genes (ARGs) may play an important role in various biological processes of PCa. The aim of this study was to identify and evaluate autophagy-related features to predict clinical outcomes in patients with PCa.
View Article and Find Full Text PDFInvest New Drugs
January 2025
Department of Pharmacy, Aichi Cancer Center Hospital, 1-1, Kanokoden, Chikusa-Ku, Nagoya, Aichi, 464-8681, Japan.
Anamorelin, a highly selective ghrelin receptor agonist, enhances appetite and increases lean body mass in patients with cancer cachexia. However, the predictors of its therapeutic effectiveness are uncertain. This study aimed to investigate the association between the Glasgow prognostic score (GPS), used for classifying the severity of cancer cachexia, the therapeutic effectiveness of anamorelin, and the feasibility of early treatment based on cancer types.
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