Changes in platelet count (PLT) are strongly associated with patient survival and may be clinically indicative of certain underlying diseases. However, there were few studies on the prognosis of patients with cancer cachexia. The purpose of this study was to investigate the relationship between PLT and 1-year survival in patients with cancer cachexia. We performed a nested case-control study of data from a multicenter clinical study of cancer. There were 252 patients with cancer cachexia whose survival time was less than or equal to 1 year and 252 patients with cancer cachexia whose survival time was more than 1 year meeting the inclusion criteria. The mortality risk and the adjusted risk were estimated by logistic regression and displayed as odds ratios (ORs) and 95% confidence intervals (95% CIs). PLT was negatively correlated with 1-year overall survival (OS) of patients with cancer cachexia (increased per standard deviation (SD): OR = 1.29; 95% CI: 1.05-1.60; = 0.018). The higher the PLT, the lower the OS of patients. When classified by dichotomy (D1 < 296×10/L, D2 ≥ 296×10/L), OS of patients in the D2 group was worse (OR = 2.18; 95% CI: 1.38-3.47; = 0.001). When classified by quartile (Q1- Q3 < 305×10/L, Q4 ≥ 305×10/L), OS of patients in the Q4 group was poorer (OR = 1.82; 95% CI: 1.14-2.94; = 0.013). In addition, patients with a low PLT (< 296×10/L) and either a high total bilirubin (TBIL) (≥ 17.1 µmol/L) or a smoking history had poor 1-year survival. Based on our primary cohort study, we conducted a survival analysis of 3130 patients with cancer cachexia and found that OS was better in patients with low PLT (< 296×10/L). PLT was negatively correlated with 1-year overall survival of patients with cancer cachexia.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8734402PMC
http://dx.doi.org/10.7150/jca.62788DOI Listing

Publication Analysis

Top Keywords

patients cancer
32
cancer cachexia
32
1-year survival
20
survival patients
16
patients
13
survival
9
cancer
9
platelet count
8
cachexia
8
252 patients
8

Similar Publications

Objective: This study aimed to evaluate and compare the clinicopathologic features of primary fallopian tubal carcinoma (PFTC) and high-grade serous ovarian cancer (HGSOC) and explore the prognostic factors of these two malignant tumors.

Methods: Fifty-seven patients diagnosed with PFTC from 2006 to 2015 and 60 patients diagnosed with HGSOC from 2014 to 2015 with complete prognostic information were identified at Women's Hospital of Zhejiang University. The clinicopathological and surgical data were collected, and the survival of the patients was followed for 5 years after surgery.

View Article and Find Full Text PDF

Background: Cancer requires interdisciplinary intersectoral care. The Care Coordination Instrument (CCI) captures patients' perspectives on cancer care coordination. We aimed to translate, adapt, and validate the CCI for Germany (CCI German version).

View Article and Find Full Text PDF

Background: Adenoid cystic carcinoma of the breast is a rare subtype, constituting less than 3.5% of primary breast carcinomas. Despite being categorized as a type of triple-negative breast cancer, it generally has a favorable prognosis.

View Article and Find Full Text PDF

Background: De-intensification of anti-cancer therapy without significantly affecting outcomes is an important goal. Omission of axillary surgery or breast radiation is considered a reasonable option in elderly patients with early-stage breast cancer and good prognostic factors. Data on avoidance of both axillary surgery and radiation therapy (RT) is scarce and inconclusive.

View Article and Find Full Text PDF

A machine learning-based model to predict POD24 in follicular lymphoma: a study by the Chinese workshop on follicular lymphoma.

Biomark Res

January 2025

Department of Hematology, The First Affiliated Hospital of Xiamen University and Institute of Hematology, School of Medicine, Xiamen University, Xiamen, 361003, P.R. China.

Background: Disease progression within 24 months (POD24) significantly impacts overall survival (OS) in patients with follicular lymphoma (FL). This study aimed to develop a robust predictive model, FLIPI-C, using a machine learning approach to identify FL patients at high risk of POD24.

Methods: A cohort of 1,938 FL patients (FL1-3a) from seventeen centers nationwide in China was randomly divided into training and internal validation sets (2:1 ratio).

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!