Comparison of Survival Outcomes and Risk Factors Between Ductal Carcinoma of the Prostate and Acinar Adenocarcinoma of the Prostate: A Population-based Propensity Score-matching Study

Machine learning prediction of overall survival in prostate adenocarcinoma using ensemble techniques

Prostate adenocarcinoma (PAC) is a complex and common cancer in males and is one of the leading causes of cancer-related death globally. PAC is a multifaceted disease that encompasses different subtypes, including acinar and ductal adenocarcinoma, small cell carcinoma, neuroendocrine tumors, and transitional cell carcinoma with each subtype presenting distinct prognostic difficulties. Therefore, predicting the overall survival (OS) rate of individuals with PAC continues to be a substantial clinical barrier due to the diverse nature of the illness, coexisting medical conditions, and constraints associated with conventional diagnostic markers. As a result, we focus on using ensemble machine learning (ML) models to predict the OS of PAC patients. We evaluated these eight (8) ensemble ML models: Random Forest (RF), AdaBoost, Gradient Boosting (GB), Extreme Gradient Boosting (XGB), LightGBM (LGBM), CatBoost, Hard Voting Classifier (HVC), and Support Vector Classifier (SVC), using the data set obtained from the Cancer Genome Atlas (TCGA) PanCancer Atlas. The ensemble ML models were evaluated using essential performance indicators, such as accuracy, precision, recall, F-1 score, and ROC AUC score. The results show that GB outperformed other models by obtaining a perfect score of 1.0 in accuracy, precision, recall, and F-1 score, and 0.99 as ROC AUC. Similarly, RF and AdaBoost exhibited robust efficiency, suggesting their potential in healthcare settings for predicting PAC survival. In conclusion, the study highlights the importance of ensemble techniques in improving prediction precision and underscores the need for further research in clinical settings.

Nomograms for predicting overall and cancer-specific survival among patients with prostatic ductal adenocarcinoma: a population-base study

BACKGROUND

Prostatic ductal adenocarcinoma (PDA) is a rare malignant tumor, and research on its clinical features and prognosis is scarce. This study aims to develop prognostic nomograms to predict the overall survival (OS) and cancer-specific survival (CSS) in patients with PDA.

RESEARCH DESIGN AND METHODS

Among the 1,049 identified patients, an 8:2 random division yielded development and validation cohorts. Univariate and multivariate Cox analyses were performed to identify independent prognostic factors, which were then incorporated into nomograms predicting 1-, 3-, and 5-year OS and CSS for patients with PDA. The prognostic nomograms were evaluated using Concordance index (C-index) and receiver operating characteristic (ROC) curve, with internal validation performed through Decision Curve Analysis (DCA).

RESULTS

Independent prognostic factors, including age, marital status, lymph node status, distant metastasis, surgery method, chemotherapy, and Gleason score, were incorporated into the developed nomograms. The results of training (C-index: OS = 0.74, CSS = 0.69; AUC value: OS = 0.822-0.892, CSS = 0.836-0.873) and internal validation (C-index: OS = 0.78, CSS = 0.77) indicated our nomograms had good performance The clinical decision curve indicated that the nomogram had a good clinical net benefit.

CONCLUSIONS

This study successfully established and validated prognostic nomograms tailored for PDA patients.

Population data study reveals pain as a possible protective factor against cerebrovascular disease in cancer patients

The purpose of this study is to investigate the relationship between chronic pain and the mortality rate of cerebrovascular disease (CVD) in cancer patients. Thus, we performed a case-control investigation was conducted by utilizing data from the Surveillance, Epidemiology, and End Results (SEER) database between 1975 and 2019. Multiple demographics, pain rating and other clinical characteristics were extracted to assess predictors for the death from CVD in cancer patients. Different machine learning algorithms were applied to construct pain-related prediction model. The analysis involved 16,850 case patients and 710,729 controls. Among cancer patients, approximately 2.3% succumbed to subsequent CVD. Cancer pain (Pain rating II) was associated with a decreased risk of CVD. Univariate and multivariate COX analyses indicated that older age at cancer diagnosis, male gender, single marital status, Black or Other race, and lack of systemic therapy correlated with a higher risk of CVD-related death. Propensity score matching revealed a significantly lower proportion of Pain rating II in the case group. The logistic regression algorithm demonstrated superior predictive ability for 5-year and 10-year CVD risk in cancer patients. Notably, survival time, age, and pain rating emerged as the top three crucial variables. This study firstly investigated pain and various risk factors for CVD in cancer patients, highlighting pain as a novel and possible protective factor for CVD. The development of a risk model based on pain could aid in identifying individuals at high risk for CVD and may inspire innovative strategies for preventing CVD in cancer patients.

Prostate ductal adenocarcinoma exhibiting a late recurrence in the anterior urethra 13 years post-total prostatectomy: a case report

BACKGROUND

Prostate ductal adenocarcinoma, a rare histology observed in 0.4-0.8% of all prostate cancers, is treated similarly to acinar adenocarcinoma but tends to have a higher likelihood of metastasis, recurrence, and poorer prognosis.

CASE PRESENTATION

A 73-year-old Asian-Japanese male presented with gross hematuria, with investigations revealing a prostate ductal adenocarcinoma. Subsequent radical prostatectomy indicated a Gleason score of 8 with no lymph node metastasis. Despite initial prostate-specific antigen level reductions post-prostatectomy and salvage radiation therapy due to recurring elevated prostate-specific antigen levels, no recurrence was evident until 13 years later. A tumor in the anterior urethra was identified as metastasis of his prostate ductal adenocarcinoma.

CONCLUSION

This report presents an uncommon case of prostate ductal adenocarcinoma exhibiting a late recurrence in the anterior urethra 13 years post-radical prostatectomy.

Implications of unconventional histological subtypes on magnetic resonance imaging and oncological outcomes in patients who have undergone radical prostatectomy

The prognostic significance of unconventional histology (UH) subtypes including intraductal carcinoma of the prostate (IDC-P), ductal adenocarcinoma, and cribriform pattern has been investigated for prostate cancer (PCa). However, little is known about magnetic resonance imaging (MRI) features and the oncological impact of tumor localization in localized PCa with UH. Clinical data of 211 patients with acinar adenocarcinoma (conventional histology [CH]) and 82 patients with UH who underwent robotic-assisted radical prostatectomy (RARP) were reviewed. Patients with UH are more likely to be older and have higher Gleason grade group, higher Prostate Imaging-Reporting and Data System (PI-RADS) v2.1 score, and larger tumor volume (TV) than those with CH. Multivariate analysis identified the presence of UH as an independent prognostic factor for progression-free survival (PFS) (hazard ration (HR) 2.41, 95% confidence interval (CI) 0.22-0.79, P = 0.0073). No significant difference in PFS was seen regarding tumor localization (transition zone [TZ] or peripheral zone [PZ]) in patients with UH (P = 0.8949), whereas PZ cancer showed shorter PFS in patients with CH (P = 0.0174). PCa with UH was associated with higher progression than PCa with CH among resection margin (RM)-negative cases (P < 0.0001). Further, increased PI-RADS v2.1 score did not correlate with larger TV in UH (P = 0.991), whereas a significant difference in TV was observed in CH (P < 0.0001). The prognostic significance of UH tumor was independent of tumor localization, and shorter PFS was observed even in RM-negative cases, indicating an aggressive subtype with micro-metastatic potential. Furthermore, UH tumors are more likely to harbor a large TV despite PI-RADS v2.1 score ≤ 3. These findings will help optimal perioperative management for PCa with UH.

A population-based propensity score matching analysis of risk factors and the impact on survival associated with refusal of cancer-directed surgery in patients with prostate cancer

Cancer-directed surgeries (CDS) play a crucial role in prostate cancer (PCa) management along with possible survival and therapeutic benefits. However, barriers such as socioeconomic factors may affect patients' decision of refusing recommended CDS. This study aimed to uncover risk factors and the impact on survival associated with CDS refusal. We retrospectively reviewed the Surveillance, Epidemiology, and End Results database for patients diagnosed with PCa between 2000 and 2019. Multiple sociodemographic and clinical characteristics were extracted to assess predictors for physicians' surgical recommendations and patients' surgical refusal, respectively. Propensity score matching was performed to balance the covariates. The impact of surgical refusal on mortality risk was also investigated. A total of 185,540 patients were included. The physician's recommendation of CDS was significantly influenced by the patient's age, race, income, home location, diagnosis year, Gleason score, prostate-specific antigen (PSA), and TNM stage. About 5.6% PCa patients refused CDS, most of whom were older, non-White race, lack of partners, living outside of metropolitan areas, with higher PSA or lower clinical TNM stage. Patients who refused CDS had an increased risk of cancer-specific mortality and overall mortality than those who performed CDS. Physicians may weigh a host of sociodemographic and clinical factors prior to making a CDS recommendation. Patients' refusal of recommended CDS affected survival and was potentially modifiable by certain sociodemographic factors. Physicians should fully consider the hindrances behind patients' CDS refusal to improve patient-doctor shared decision-making, guide patients toward the best alternative and achieve better outcomes.

Genomic Evolution and Transcriptional Changes in the Evolution of Prostate Cancer into Neuroendocrine and Ductal Carcinoma Types

Prostate cancer is typically of acinar adenocarcinoma type but can occasionally present as neuroendocrine and/or ductal type carcinoma. These are associated with clinically aggressive disease, and the former often arises on a background of androgen deprivation therapy, although it can also arise de novo. Two prostate cancer cases were sequenced by exome capture from archival tissue. Case 1 was de novo small cell neuroendocrine carcinoma and ductal adenocarcinoma with three longitudinal samples over 5 years. Case 2 was a single time point after the development of treatment-related neuroendocrine prostate carcinoma. Case 1 showed whole genome doubling in all samples and focal amplification of AR in all samples except the first time point. Phylogenetic analysis revealed a common ancestry for ductal and small cell carcinoma. Case 2 showed 13q loss (involving RB1) in both adenocarcinoma and small cell carcinoma regions, and 3p gain, 4p loss, and 17p loss (involving TP53) in the latter. By using highly curated samples, we demonstrate for the first time that small-cell neuroendocrine and ductal prostatic carcinoma can have a common ancestry. We highlight whole genome doubling in a patient with prostate cancer relapse, reinforcing its poor prognostic nature.