The Correlation Between Platelet Count and Survival in Prostate Cancer

Mezei, Tünde; Bőde, Imre; Tenke, Péter; Jósa, Valéria; Merkel, Keresztély; Szilasi, Zsuzsanna; Tordai, Attila; Máthé, Domokos; Baranyai, Zsolt

doi:10.2147/rru.s359715

Cited by 4 publications

(2 citation statements)

References 53 publications

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“…Sylman et al reported a significant correlation between increased PLT counts and reduced overall survival in patients with PCa, suggesting that the PLT count could serve as a valuable prognostic indicator for prostate cancer 38 . Nevertheless, in another study, the researchers showed no association between elevated PLT counts and the clinical-pathological characteristics or prognosis of PCa patients, which is consistent with our study findings 39 . The discrepant findings among studies could potentially be attributed to the absence of standardized inclusion and exclusion criteria, differences in the patient populations investigated, as well as variations in the laboratory testing methods and reagents employed.…”

Section: Discussionsupporting

confidence: 92%

Coagulation markers as independent predictors of prostate cancer aggressiveness: a retrospective cohort study

Lei,

Zhang,

Deng

et al. 2023

Sci Rep

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Coagulation system activation is commonly observed in tumor patients, including prostate cancer (PCa), with coagulation markers proposed as potential prognostic indicators for cancer severity. However, the correlation between these markers and clinicopathological features in PCa remains unclear. Thus, this study investigates the association between comprehensive coagulation markers and clinicopathological characteristics in PCa patients. A retrospective evaluation of 162 PCa patients diagnosed and categorized into low-intermediate-risk or high-risk groups based on clinical and pathological features was conducted. Coagulation markers, including fibrinogen (FIB), d-dimer (DD), activated partial thromboplastin time (APTT), prothrombin time (PT), prothrombin activity (PTA), thrombin time (TT), platelet count (PLT), and international normalized ratio (INR), were assessed. Univariate and multivariate logistic regression analyses were performed to determine associations with clinicopathological features. FIB and DD were confirmed as independent factors associated with high-risk PCa. Furthermore, FIB and DD levels showed significant positive correlations with clinical parameters, including PSA levels, ISUP grade, T stage, N stage, and M stage. Our findings suggest that FIB and DD hold promise as independent prognostic biomarkers for risk stratification in PCa. These coagulation markers may aid in assessing PCa severity and guiding personalized treatment strategies.

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Section: Discussionsupporting

confidence: 92%

Coagulation markers as independent predictors of prostate cancer aggressiveness: a retrospective cohort study

Lei,

Zhang,

Deng

et al. 2023

Sci Rep

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“…Prostate cancer (PCa) is the most common cancer diagnosed in men accounting alone for 26% of diagnoses in 2021 in the United States, according to population-based cancer incidence data collected by the National Cancer Institute's (NCI's) Surveillance, Epidemiology, and End Results (SEER) program. 1,2 Europe had an all-age incidence ASR of 63 per100000males (473 334 estimated new cases in the year 2020). 3 The role of chronic inflammation in carcinogenesis has been widely studied, and it is estimated that it may contribute to the development of up to 20% of all adult cancers.…”

Section: Introductionmentioning

confidence: 99%

Correlation Between Long-Term Acetylsalicylic Acid Use and Prostate Cancer Screening with PSA. Should We Reduce the PSA Cut-off for Patients in Chronic Therapy? A Multicenter Study

Mantica¹,

Chierigo²,

Cassim³

et al. 2022

RRU

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Purpose To evaluate the prostate cancer (PCa) detection rate in men with chronic use of Aspirin and to compare it with the detection rate of non-users. Patients and Methods Prospectively maintained database regarding patients undergoing prostate biopsy over the last 10 years in five institutions. Patients were divided into two groups according to their exposure to Aspirin. We relied on multivariable linear and logistic regression models to test whether Aspirin administration was associated with lower PSA values at prostate biopsy, higher PCa diagnosis, and higher Gleason Grade Grouping (GGG) at biopsy. Results Were identified 1059 patients, of whom 803 (76%) did not take Aspirin vs 256 (24%) were taking it. In multivariable log-linear regression analysis, Aspirin administration was associated with lower PSA levels (OR 0.83, 95% CI 0.71–0.97, p = 0.01), after controlling for age, prostate volume, smoking history, associated inflammation at prostate biopsy, presence of PCa at biopsy, and GGG. In multivariable logistic regression analysis, Aspirin administration was not found to be a predictor of PCa at prostate biopsy (OR 1.40, 95% CI 0.82–2.40, p = 0.21) after controlling for age, PSA, smoking history, prostate volume, findings at digital rectal examination and the number of biopsy cores. In patients with PCa at prostate biopsy (n = 516), Aspirin administration was found to predict higher GGG (OR 2.24, 95% CI 1.01–4.87, p = 0.04). Conclusion Aspirin administration was found to be a predictor of more aggressive GGG. These findings suggest that a lower PSA threshold should be considered in patients taking Aspirin, as, despite low PSA levels, they might harbour aggressive PCa.

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Improving platelet‐RNA‐based diagnostics: a comparative analysis of machine learning models for cancer detection and multiclass classification

Jopek,

Pastuszak,

Sieczczyński

et al. 2024

Molecular Oncology

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Liquid biopsy demonstrates excellent potential in patient management by providing a minimally invasive and cost‐effective approach to detecting and monitoring cancer, even at its early stages. Due to the complexity of liquid biopsy data, machine‐learning techniques are increasingly gaining attention in sample analysis, especially for multidimensional data such as RNA expression profiles. Yet, there is no agreement in the community on which methods are the most effective or how to process the data. To circumvent this, we performed a large‐scale study using various machine‐learning techniques. First, we took a closer look at existing datasets and filtered out some patients to assert data collection quality. The final data collection included platelet RNA samples acquired from 1397 cancer patients (17 types of cancer) and 354 asymptomatic, presumed healthy, donors. Then, we assessed an array of different machine‐learning models and techniques (e.g., feature selection of RNA transcripts) in pan‐cancer detection and multiclass classification. Our results show that simple logistic regression performs the best, reaching a 68% cancer detection rate at a 99% specificity level, and multiclass classification accuracy of 79.38% when distinguishing between five cancer types. In summary, by revisiting classical machine‐learning models, we have exceeded the previously used method by 5% and 9.65% in cancer detection and multiclass classification, respectively. To ease further research, we open‐source our code and data processing pipelines (https://gitlab.com/jopekmaksym/improving‐platelet‐rna‐based‐diagnostics), which we hope will serve the community as a strong baseline.

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The Correlation Between Platelet Count and Survival in Prostate Cancer

Cited by 4 publications

References 53 publications

Coagulation markers as independent predictors of prostate cancer aggressiveness: a retrospective cohort study

Coagulation markers as independent predictors of prostate cancer aggressiveness: a retrospective cohort study

Correlation Between Long-Term Acetylsalicylic Acid Use and Prostate Cancer Screening with PSA. Should We Reduce the PSA Cut-off for Patients in Chronic Therapy? A Multicenter Study

Improving platelet‐RNA‐based diagnostics: a comparative analysis of machine learning models for cancer detection and multiclass classification

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