Prostate Cancer in Older Adults: Risk of Clinically Meaningful Disease, the Role of Screening and Special Considerations

Association between Charlson comorbidity index and survival outcomes in patients with prostate cancer: A meta-analysis

Objective

This meta-analysis aimed to assess the influence of comorbidity, as assessed by the Charlson comorbidity index (CCI), on survival outcomes in patients with prostate cancer (PCa).

Methods

We conducted a comprehensive search of the PubMed, Web of Science, and Embase databases to identify studies that examined the association between CCI-defined comorbidity and survival outcomes in PCa patients. We employed a random effect model to merge adjusted hazard ratios (HR) with 95 % confidence intervals (CI) for survival outcomes.

Results

Sixteen studies reporting on 17 articles, which collectively included 457,256 patients. For the presence (CCI score ≥1) versus absence (CCI score of 0) of comorbidity, the pooled HR was 1.59 (95 % CI 1.43-1.77) for all-cause mortality, 0.98 (95 % CI 0.90-1.08) for PCa-specific mortality, and 1.88 (95 % CI 1.61-2.21) for other-cause mortality. When compared to a CCI score of 0, the pooled HR of all-cause mortality was 1.30 (95 % CI 1.18-1.44) for a CCI score of 1, 1.65 (95 % CI 1.37-2.00) for a CCI score ≥2, and 1.75 (95 % CI 1.57-1.95) for a CCI score ≥3. Additionally, the pooled HR of other cause mortality was 1.53 (95 % CI 1.41-1.67) for a CCI score of 1, 1.93 (95 % CI 1.74-2.75) for a CCI score ≥2, and 3.95 (95 % CI 2.13-7.34) for a CCI score ≥3.

Conclusions

Increased comorbidity, as assessed by the CCI, significantly predicts all-cause and other-cause mortality in patients with PCa, but not PCa-specific mortality. The risk of all-cause and other-cause mortality increases with the burden of comorbidity.

Advancing prostate cancer detection: a comparative analysis of PCLDA-SVM and PCLDA-KNN classifiers for enhanced diagnostic accuracy

This investigation aimed to assess the effectiveness of different classification models in diagnosing prostate cancer using a screening dataset obtained from the National Cancer Institute's Cancer Data Access System. The dataset was first reduced using the PCLDA method, which combines Principal Component Analysis and Linear Discriminant Analysis. Two classifiers, Support Vector Machine (SVM) and k-Nearest Neighbour (KNN), were then applied to compare their performance. The results showed that the PCLDA-SVM model achieved an impressive accuracy rate of 97.99%, with a precision of 0.92, sensitivity of 92.83%, specificity of 97.65%, and F1 score of 0.93. Additionally, it demonstrated a low error rate of 0.016 and a Matthews Correlation Coefficient (MCC) and Kappa coefficient of 0.946. On the other hand, the PCLDA-KNN model also performed well, achieving an accuracy of 97.8%, precision of 0.93, sensitivity of 93.39%, specificity of 97.86%, an F1 score of 0.92, a high MCC and Kappa coefficient of 0.98, and an error rate of 0.006. In conclusion, the PCLDA-SVM method exhibited improved efficacy in diagnosing prostate cancer compared to the PCLDA-KNN model. Both models, however, showed promising results, suggesting the potential of these classifiers in prostate cancer diagnosis.

China county-based prostate specific antigen screening for prostate cancer and a cost-effective analysis

Background

Prostate cancer is one of the most common malignant tumors worldwide, and is the third-leading cause of cancer death in men. Nearly 70% of new prostate cancer patients in China are locally advanced or widely metastatic with poor prognosis. Providing active treatment to early stage prostate cancer patients can improve the prognosis of prostate cancer patients. Thus, this study sought to evaluate the economy of early prostate specific antigen (PSA) screening for high-risk prostate cancer.

Methods

Based on the data collected from the PSA screening activities of 11 county hospitals from October 2019 to April 2021, this study evaluated a high-risk prostate cancer population who received PSA screening and their quality of life and economy. The screening population comprised males aged over 50 years. All screening patients were tested for PSA. If the PSA value is unnormal, a further diagnosis based on magnetic resonance imagining (MRI) or a transrectal ultrasound-guided prostate biopsy were performed. The decision-tree and Markov model was used to simulate the process of disease development of high-risk prostate cancer patients who underwent screenings and those who did not, and the incremental cost-effectiveness ratio was also evaluated.

Results

A total of 13,726 men received a PSA screening. Of these, 1,062 men had abnormal PSA values, and 73 of these were diagnosed with prostate cancer. Of these 73 patients, 40, 21, and 12 had early stage, mid-stage, and late-stage prostate cancer, respectively. Compared to the patients unscreened, the 1,000 patients who received an early PSA screening increased their quality-adjusted life year (QALY) by 15.69 years; however, each QALY had an additional cost of 38,550 yuan, which was lower than the willingness to pay threshold of 72,447 yuan (per capita gross domestic product in 2020).

Conclusions

For high-risk prostate cancer patients, early screenings have a cost-effective advantage over no screenings. Thus, early screening should be vigorously promoted for high-risk prostate cancer patients.