[Epidemiological signatures and surveillance bias in cancer]. / Signatures épidémiologiques et biais de surveillance du cancer.

Surveillance bias occurs when variations in cancer incidence are the result of changes in screening or diagnostic practices rather than increases in the true occurrence of cancer. This bias is linked to the issue of overdiagnosis and can be apprehended by looking at epidemiological signatures of cancer. We explain the concept of epidemiological signatures using the examples of melanoma and of lung and prostate cancer. Accounting for surveillance bias is particularly important for assessing the true burden of cancer and for accurately communicating cancer information to the population and decision-makers.

Le biais de surveillance se produit lorsque les variations d'incidence d'un cancer sont le résultat d'un changement dans les pratiques de dépistage ou de diagnostic plutôt que d'une augmentation de la fréquence réelle de ce cancer. Ce biais est lié au concept du surdiagnostic et peut être appréhendé en examinant les signatures épidémiologiques des cancers. Nous expliquons le concept de signature épidémiologique à l'aide des exemples du mélanome et des cancers du poumon et de la prostate. La prise en compte des biais de surveillance est particulièrement importante pour évaluer le fardeau réel du cancer et communiquer avec précision l'information sur le cancer à la population et aux décideurs.

Biomolecule-regulation of fluorescent probe signaling: Homogeneous rapid portable protease sensing in serum.

BACKGROUND: As is well documented, prostate cancer (PCa) being the second most prevalent cancer in men worldwide, emphasizing the importance of early diagnosis for prognosis. However, conventional prostate-specific antigen (PSA) testing lacks sufficient diagnostic efficiency due to its relatively low sensitivity and limited detection range. Mounting evidence suggests that matrix metalloproteinase 9 (MMP-9) expression increases with the aggressive behavior of PCa, highlighting the significance of detecting the serum level of MMP-9 in patients. Developing a non-immune rapid, portable MMP-9 detection strategy and investigating its representativeness of PCa serum markers hold considerable implications. RESULTS: Herein, our study developed a simple, homogeneous dual fluorescence and smartphone-assisted red-green-blue (RGB) visualization peptide sensor of MMP-9, utilizing cadmium telluride quantum dots (CdTe QDs) and calcein as signal reporters. The essence of our approach revolves around the proteolytic ability of MMP-9, exploiting the selective recognition of molecule-Cu2+ complexes with different molecular weights by CdTe QDs and calcein. Under optimized conditions, the limits of detection (LODs) for MMP-9 were 0.5 pg/mL and 6 pg/mL using fluorescence and RGB values readouts, respectively. Indeed, this strategy exhibited robust specificity and anti-interference ability. MMP-9 was quantified in 42 clinical serum samples via dual-fluorescence analysis, with 12 samples being visually identified with a smartphone. According to receiver operating characteristic curve (ROC) analysis, its sensitivity and specificity were 90 % and 100 %, respectively, with an area under curve (AUC) value of 0.903. SIGNIFICANCE AND NOVELTY: Of note, the results of the aforementioned analysis were highly consistent with the serum level of PSA, clinical color Doppler flow imaging (CDFI), and histopathological results. Therefore, this simple, rapid, homogeneous fluorescence and visualization strategy can reliably measure MMP-9 levels and exhibit promising potential in point-of-care testing (POCT) applications for PCa patients.

Association between lymphocyte-to-monocyte ratio and prostate cancer in men: A population-based study.

Using the novel inflammatory biomarker lymphocyte-to-monocyte ratio (LMR), this work aimed to look into any potential connections between LMR and prostate cancer (PCa). A cross-sectional research investigation was conducted on 7706 male participants involved in the National Health and Nutrition Examination Survey from 2001 to 2010. Multivariate logistic regression modeling investigated the relationship between LMR levels and PCa risk. Furthermore, threshold analysis, subgroup analysis, interaction testing, and smoothed curve fitting were carried out. A significant negative correlation was seen between LMR and PCa risk (OR = 0.79, 95% CI: 0.65-0.97, P = .0002), even after controlling for potential confounding factors. A significant nonlinear negative correlation with a threshold effect and a breakpoint of 4.86 was found by smooth curve fitting between LMR and PCa. Subgroup analysis revealed a significant interaction (P for interaction = 0.0448) between the negative correlation between PCa and LMR about hypertension. Moreover, additional stratified smoothed curve fitting demonstrated a statistically significant inverse relationship between PCa risk and LMR. According to our findings, there is a substantial inverse relationship between PCa risk and LMR level. The inflammatory response-related index is quick, easy to use, and offers some clinical references. However, more extensive prospective investigations are required to confirm the involvement of LMR levels in PCa.

Multi-omics analysis and experimental validation of the value of monocyte-associated features in prostate cancer prognosis and immunotherapy.

Background: Monocytes play a critical role in tumor initiation and progression, with their impact on prostate adenocarcinoma (PRAD) not yet fully understood. This study aimed to identify key monocyte-related genes and elucidate their mechanisms in PRAD. Method: Utilizing the TCGA-PRAD dataset, immune cell infiltration levels were assessed using CIBERSORT, and their correlation with patient prognosis was analyzed. The WGCNA method pinpointed 14 crucial monocyte-related genes. A diagnostic model focused on monocytes was developed using a combination of machine learning algorithms, while a prognostic model was created using the LASSO algorithm, both of which were validated. Random forest and gradient boosting machine singled out CCNA2 as the most significant gene related to prognosis in monocytes, with its function further investigated through gene enrichment analysis. Mendelian randomization analysis of the association of HLA-DR high-expressing monocytes with PRAD. Molecular docking was employed to assess the binding affinity of CCNA2 with targeted drugs for PRAD, and experimental validation confirmed the expression and prognostic value of CCNA2 in PRAD. Result: Based on the identification of 14 monocyte-related genes by WGCNA, we developed a diagnostic model for PRAD using a combination of multiple machine learning algorithms. Additionally, we constructed a prognostic model using the LASSO algorithm, both of which demonstrated excellent predictive capabilities. Analysis with random forest and gradient boosting machine algorithms further supported the potential prognostic value of CCNA2 in PRAD. Gene enrichment analysis revealed the association of CCNA2 with the regulation of cell cycle and cellular senescence in PRAD. Mendelian randomization analysis confirmed that monocytes expressing high levels of HLA-DR may promote PRAD. Molecular docking results suggested a strong affinity of CCNA2 for drugs targeting PRAD. Furthermore, immunohistochemistry experiments validated the upregulation of CCNA2 expression in PRAD and its correlation with patient prognosis. Conclusion: Our findings offer new insights into monocyte heterogeneity and its role in PRAD. Furthermore, CCNA2 holds potential as a novel targeted drug for PRAD.

Cancer health awareness through screening and education: A community approach to healthy equity.

BACKGROUND: The Cancer Health Awareness through screeNinG and Education (CHANGE) initiative delivers cancer awareness education with an emphasis on modifiable risk factors and navigation to screening for prostate, breast, and colorectal cancers to residents of public housing communities who experience significant negative social determinants of health. METHODS: Residents of five communities participated. Community advisory board members were recruited and provided feedback to local environmental change projects, recruitment, and community engagement at each site. At each site, four education sessions were provided by trained facilitators on cancer risk factors and etiology, racial disparities, eligibility for cancer screening, and participation in clinical trials. Attendance, knowledge, attitudes and beliefs about cancer, and height, weight, and waist circumference were measured at baseline and 1-week post-CHANGE sessions. RESULTS: 90 residents (60% 65 and older years old, 33% male, 60% High School education, 93% AA) participated in the program. 95% completed post-intervention evaluation. Participants were eligible for breast (n = 12), prostate (n = 15), and colorectal screening (n = 25) based on American Cancer Society guidelines, and 22 for tobacco cessation; 21 participants accepted navigation assistance for these services. At post-test, participants significantly increased in knowledge and behaviors around obesity/overweight risk for cancer, nutrition, and physical activity. Colorectal, prostate, and breast cancer knowledge scores also increased, but were not significant. CONCLUSIONS: CHANGE participants demonstrated improved health knowledge and intentions to improve their modifiable health behaviors. Participants reported being motivated and confident in seeking preventive care and satisfaction with community engagement efforts. Replication of this project in similar communities may improve knowledge and health equity among underserved populations.

Prostate cancer diagnosis based on multi-parametric MRI, clinical and pathological factors using deep learning.

Prostate cancer is one of the most common and fatal diseases among men, and its early diagnosis can have a significant impact on the treatment process and prevent mortality. Since it does not have apparent clinical symptoms in the early stages, it is difficult to diagnose. In addition, the disagreement of experts in the analysis of magnetic resonance images is also a significant challenge. In recent years, various research has shown that deep learning, especially convolutional neural networks, has appeared successfully in machine vision (especially in medical image analysis). In this research, a deep learning approach was used on multi-parameter magnetic resonance images, and the synergistic effect of clinical and pathological data on the accuracy of the model was investigated. The data were collected from Trita Hospital in Tehran, which included 343 patients (data augmentation and learning transfer methods were used during the process). In the designed model, four different types of images are analyzed with four separate ResNet50 deep convolutional networks, and their extracted features are transferred to a fully connected neural network and combined with clinical and pathological features. In the model without clinical and pathological data, the maximum accuracy reached 88%, but by adding these data, the accuracy increased to 96%, which shows the significant impact of clinical and pathological data on the accuracy of diagnosis.

Decision regret after prostate biopsy for prostate cancer diagnosis: a Korean multicenter cohort study.

BACKGROUND: Many people struggle with the choice in a series of processes, from prostate cancer (PCa) diagnosis to treatment. We investigated the degree of regret after the prostate biopsy (PBx) and relevant factors in patients recommended for biopsy for suspected PCa. METHODS: From 06/2020 to 05/2022, 198 people who performed PBx at three institutions were enrolled and analyzed through a questionnaire before and after biopsy. Before the biopsy, a questionnaire was conducted to evaluate the sociodemographic information, anxiety scale, and health literacy, and after PBx, another questionnaire was conducted to evaluate the decision regret scale. For patients diagnosed as PCa after biopsy, a questionnaire was conducted when additional tests were performed at PCa staging work-up. RESULTS: 190 patients answered the questionnaire before and after PBx. The mean age was 66.2 ± 7.8 years. Overall, 5.5% of men regretted biopsy, but there was no significant difference between groups according to the PCa presence. Multivariate analysis, to identify predictors for regret, revealed that the case when physicians did not properly explain what the prostate-specific antigen (PSA) test was like and what PSA elevation means (OR 20.57, [95% CI 2.45-172.70], p = 0.005), low media literacy (OR 10.01, [95% CI 1.09-92.29], p = 0.042), and when nobody to rely on (OR 8.49, [95% CI 1.66-43.34], p = 0.010) were significantly related. CONCLUSIONS: Overall regret related to PBx was low. Decision regret was more significantly related to media literacy rather than to educational level. For patients with relatively low media literacy and fewer people to rely on in case of serious diseases, more careful attention and counseling on PBx, including a well-informed explanation on PSA test, is helpful.

Urinary PSA-ZINC biomarker outperforms standard of care in early detection of prostate cancer.

BACKGROUND: Urine is a promising biological fluid for prostate cancer (PCa) diagnostics due to its non-invasive collection and wide range of biomarkers. The aim of this study was to assess the role of urinary PSA (uPSA) and urinary Zinc (uZinc) as biomarkers for the diagnosis of PCa in combination with routine parameters of standard of care (SOC - blood PSA, abnormal DRE, age) and MRI in patients candidates for prostate biopsy. METHODS: Urine samples after prostatic massages were collected from men with suspected PCa scheduled for prostate biopsy. Quantification of uPSA was performed by ECLIA platform and confirmed by ELISA assay, while uZinc measurement was evaluated by ICP-MS and confirmed by colorimetric in vitro assay. Six multivariate logistic regression analysis were performed to assess diagnostic performance of uPSA and uZinc (urine), SOC and MRI alone, and combination of MRI+SOC, MRI+urine and SOC+MRI+urine. The discriminative power of the logistic models was assessed by calculating the area under the receiver operating characteristic (ROC) curves (AUC). RESULTS: Two hundred thirty-eight patients were included in the analysis; 145 of them were diagnosed with PCa. Urine test showed a better discrimination of HS from CP, in respect of uPSA and uZinc alone, both for PCa of any grade and Gleason Score ≥7 (4+3) (AUC 0.804 and 0.823 respectively). ROC curve combining SOC+MRI+urine showed an AUC=0.882, that is statistically different from SOC or MRI alone, or MRI+SOC (P=0.0001, P=0.0001, and P=0.008 respectively). PCa risk algorithm designed considering SOC+MRI+urine results in potential reduction of 57% of unnecessary biopsies compared to the current standard parameters. CONCLUSIONS: The loss of uPSA and Zinc production and secretion during neoplastic transformation of the prostate could potentially represent a hallmark of PCa. Its combination with age, PSA and DRE, as well as with mpMRI could represent an interesting approach to improve the diagnostic accuracy of PCa.

Prostate Cancer Among Black Men in Canada.

Importance: Prostate cancer is a prevalent disease among men worldwide, exhibiting substantial heterogeneity in presentation and outcomes influenced by various factors, including race and ethnicity. Disparities in incidence, stage at diagnosis, and survival rates have been observed between Black men and those of other races and ethnicities. Objective: To compare prostate cancer outcomes between Black men and men with other race (Asian, Hispanic, Indigenous, Middle Eastern, White, Multiracial, and Other) in a universal health care system, with race and ethnicity self-reported. Design, Setting, and Participants: This was a prospective, observational cohort study of men diagnosed with prostate cancer between June 1, 2014, and August 28, 2023, who self-identified race and ethnicity. Participants included men who had been prospectively enrolled in the Alberta Prostate Cancer Research Initiative from the 2 major urology referral centers in Alberta (University of Alberta and University of Calgary). All men with prostate cancer enrolled in the initiative were included. Exposure: Race and ethnicity. Main Outcomes and Measures: The primary outcome was the stage and grade of prostate cancer at diagnosis. Further outcomes included age and prostate-specific antigen level at diagnosis, initial treatment modality, time from diagnosis to initial treatment, and prostate cancer-specific, metastasis-free, and overall survivals. Results: A total of 6534 men were included; 177 (2.7%) were Black, and 6357 (97.3%) had another race or ethnicity. Men who identified as Black were diagnosed with prostate cancer at an earlier age (mean [SD], 62.0 [8.2] compared with 64.6 [7.7] years; P < .001) and had a lower Charlson Comorbidity Index rating (14% compared with 7% ≤ 1; P < .001) compared with men of other races. Men who identified as Black had similar prostate-specific antigen levels at diagnosis, TNM category (74% vs 74% with T1-T2; P = .83) and Gleason Grade Group (34% compared with 35% Gleason Grade Group 1; P = .63). Black men had similar rates of prostate cancer-specific (hazard ratio [HR], 1.10; 95% CI, 0.41-2.97; P = .85), metastasis-free (HR, 0.88; 95% CI, 0.42-1.46; P = .44), and overall (HR, 0.55; 95% CI, 0.25-1.24; P = .15) survival. Conclusions and Relevance: The findings of this cohort study suggest that Black men, despite being diagnosed at a younger age, experience comparable prostate cancer outcomes compared with men of other races.

Identification of metastasis-related genes for predicting prostate cancer diagnosis, metastasis and immunotherapy drug candidates using machine learning approaches.

BACKGROUND: Prostate cancer (PCa) is the second leading cause of tumor-related mortality in men. Metastasis from advanced tumors is the primary cause of death among patients. Identifying novel and effective biomarkers is essential for understanding the mechanisms of metastasis in PCa patients and developing successful interventions. METHODS: Using the GSE8511 and GSE27616 data sets, 21 metastasis-related genes were identified through the weighted gene co-expression network analysis (WGCNA) method. Subsequent functional analysis of these genes was conducted on the gene set cancer analysis (GSCA) website. Cluster analysis was utilized to explore the relationship between these genes, immune infiltration in PCa, and the efficacy of targeted drug IC50 scores. Machine learning algorithms were then employed to construct diagnostic and prognostic models, assessing their predictive accuracy. Additionally, multivariate COX regression analysis highlighted the significant role of POLD1 and examined its association with DNA methylation. Finally, molecular docking and immunohistochemistry experiments were carried out to assess the binding affinity of POLD1 to PCa drugs and its impact on PCa prognosis. RESULTS: The study identified 21 metastasis-related genes using the WGCNA method, which were found to be associated with DNA damage, hormone AR activation, and inhibition of the RTK pathway. Cluster analysis confirmed a significant correlation between these genes and PCa metastasis, particularly in the context of immunotherapy and targeted therapy drugs. A diagnostic model combining multiple machine learning algorithms showed strong predictive capabilities for PCa diagnosis, while a transfer model using the LASSO algorithm also yielded promising results. POLD1 emerged as a key prognostic gene among the metastatic genes, showing associations with DNA methylation. Molecular docking experiments supported its high affinity with PCa-targeted drugs. Immunohistochemistry experiments further validated that increased POLD1 expression is linked to poor prognosis in PCa patients. CONCLUSIONS: The developed diagnostic and metastasis models provide substantial value for patients with prostate cancer. The discovery of POLD1 as a novel biomarker related to prostate cancer metastasis offers a promising avenue for enhancing treatment of prostate cancer metastasis.

Digital Rectal Exam in Prostate Cancer Screening and Elevated PSA Work-up-Is there a role anymore?

PURPOSE OF REVIEW: Prostate cancer (PCa) screening tools, particularly digital rectal examination (DRE), are under scrutiny. This review assesses the utility of DRE in PCa screening. RECENT FINDINGS: Recent studies reaffirm the DRE's sensitivity and specificity, a higher PCa detection rate with PSA in conjunction with DRE, and a slightly elevated risk of clinically significant PCa (CSPC) in those with elevated PSA and suspicious DRE. Studies confirm high accuracy of MRI in identifying CSPC, with ongoing research exploring its screening potential. DRE alone lacks accuracy for PCa screening, often resulting in missed diagnoses and unnecessary biopsies. Its supplementary use with PSA marginally increases detection rates of identifying a small percentage of CSPC, but the benefit remains questionable. Emerging evidence suggests MRI has the potential as a superior screening tool compared to DRE, although direct comparative studies are lacking. Overall, the DRE has a limited role in current PCa screening.

Prognosis and diagnosis of prostate cancer based on hypergraph regularization sparse least partial squares regression algorithm.

BACKGROUND: Prostate cancer (PCa) is a malignant tumor of the male reproductive system, and its incidence has increased significantly in recent years. This study aimed to further identify candidate biomarkers with prognostic and diagnostic significance by integrating gene expression and DNA methylation data from PCa patients through association analysis. MATERIAL AND METHODS: To this end, this paper proposes a sparse partial least squares regression algorithm based on hypergraph regularization (HR-SPLS) by integrating and clustering two kinds of data. Next, module 2, with the most significant weight, was selected for further analysis according to the weight of each module related to DNA methylation and mRNAs. Based on the DNA methylation sites in module 2, this paper uses multiple machine learning methods to construct a PCa diagnosis-related model of 10-DNA methylation sites. RESULTS: The results of Receiver Operating Characteristic (ROC) analysis showed that the DNA methylation-related diagnostic model we constructed could diagnose PCa patients with high accuracy. Subsequently, based on the mRNAs in module 2, we constructed a prognostic model for 7-mRNAs (MYH11, ACTG2, DDR2, CDC42EP3, MARCKSL1, LMOD1, and MYLK) using multivariate Cox regression analysis. The prognostic model could predict the disease free survival of PCa patients with moderate to high accuracy (area under the curve (AUC) =0.761). In addition, Gene Set EnrichmentAnalysis (GSEA) and immune analysis indicated that the prognosis of patients in the risk group might be related to immune cell infiltration. CONCLUSIONS: Our findings may provide new methods and insights for identifying disease-related biomarkers by integrating DNA methylation and gene expression data.

Quality of Life in Patients and Their Spouses and Cohabitating Partners in the Year Following a Cancer Biopsy (the Couples Cope Study): Protocol for a Prospective Observational Study.

BACKGROUND: Receiving a diagnosis of cancer is a profound and often very stressful experience. Few studies have prospectively recruited patients prior to receiving a new diagnosis of cancer and included spouses or partners. OBJECTIVE: The aim of the Couples Cope Study is to understand the impact of undergoing a diagnostic biopsy and receiving a new cancer diagnosis on quality of life (QoL) in both patients and their spouses or partners, as well as on the quality of their relationship. This protocol paper describes the study design and assesses the feasibility of recruitment and retention. METHODS: Study staff reviewed the schedules of collaborating physicians using specific encounter codes to identify patients scheduled for breast or prostate biopsies. Potential participants were prescreened via the electronic health record and sent a recruitment letter at least 2 to 3 weeks prior to their biopsy procedure. Patients subsequently underwent a phone screening to determine eligibility. Patients who enrolled provided study staff with contact information for their spouses or partners. All consent forms were completed online. Surveys were completed online prior to receiving the biopsy results (baseline), and at 1, 3, 6, and 9 months after the biopsy. Study staff engaged in ongoing, personalized contact with participants and sent assessment completion reminders via phone and email. RESULTS: A total of 2294 patients undergoing a breast or prostate biopsy were identified and 69% (n=1582) were eligible for phone screening following electronic health record prescreening. Of the 431 patients who underwent phone screening, 75% (n=321) were eligible to participate. Of the eligible patients, 72% (n=231) enrolled and 82% (n=190) of enrolled patients had an accompanying partner or spouse who also enrolled. A total of 77% (34/44) of patients who received a cancer diagnosis and 72% (26/36) of their spouses or partners were retained through 9 months, while 80% (53/66) of patients who received a benign diagnosis and 68% (42/62) of their partners were retained. CONCLUSIONS: Prospective recruitment of patients undergoing diagnostic biopsy and their partners is feasible and requires both strategic collaboration with providers and concerted prescreening and recruitment efforts by study staff. Importantly, this study was able to conduct all study activities online without disrupting clinical workflow and without requiring patients and their spouses or partners to come into the laboratory. Consideration should be given to the ratio of biopsies to cancer diagnoses, which can vary significantly by cancer type. Prospective studies are needed and can inform our ability to provide effective support earlier to couples facing a possible cancer diagnosis. Future studies should examine other tumor types that have received less attention in QoL studies, include behavioral and neurobiological assessments beyond self-report measures, and follow couples beyond 9 months in order to examine long-term effects on QoL. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/52361.

Integrative bioinformatics approach yields a novel gene expression risk model for prognosis and progression prediction in prostate cancer.

Prostate cancer (PCa), a prevalent malignancy among elderly males, exhibits a notable rate of advancement, even when subjected to conventional androgen deprivation therapy or chemotherapy. An effective progression prediction model would prove invaluable in identifying patients with a higher progression risk. Using bioinformatics strategies, we integrated diverse data sets of PCa to construct a novel risk model predicated on gene expression and progression-free survival (PFS). The accuracy of the model was assessed through validation using an independent data set. Eight genes were discerned as independent prognostic factors and included in the prediction model. Patients assigned to the high-risk cohort demonstrated a diminished PFS, and the areas under the curve of our model in the validation set for 1-year, 3-year, and 5-year PFS were 0.9325, 0.9041 and 0.9070, respectively. Additionally, through the application of single-cell RNA sequencing to two castration-related prostate cancer (CRPC) samples and two hormone-related prostate cancer (HSPC) samples, we discovered that luminal cells within CRPC exhibited an elevated risk score. Subsequent molecular biology experiments corroborated our findings, illustrating heightened SYK expression levels within tumour tissues and its contribution to cancer cell migration. We found that the knockdown of SYK could inhibit migration in PCa cells. Our progression-related risk model demonstrated the potential prognostic value of SYK and indicated its potential as a target for future diagnosis and treatment strategies in PCa management.

Evaluation of the clinical application value of cytokine expression profiles in the differential diagnosis of prostate cancer.

BACKGROUND: The significance of tumor-secreted cytokines in tumor development has gained substantial attention. Nevertheless, the precise role of tumor-related inflammatory cytokines in prostate cancer (PCa) remains ambiguous. OBJECTIVES: To gain deeper insights into the inflammatory response in the process of PCa. METHODS: A total of 233 cases were collected, including 80 cases of prostate hyperplasia as disease control, 65 cases of postoperative prostate cancer and 36 cases of prostate cancer as PCa group. Additionally, 52 patients undergoing physical examinations during the same period were collected as the healthy control. The levels of 12 inflammatory cytokines in peripheral blood samples were analyzed using flow cytometric bead array technology. The levels of total prostate-specific antigen (TPSA) and free prostate-specific antigen (FPSA) in peripheral blood samples were analyzed using electrochemiluminescence technology. RESULTS: Our findings revealed significant increases in serum IL-8 levels in PCa group compared to the healthy control group. Additionally, IL-6, IL-10, IFN-γ and IL-12p70 levels were markedly elevated in the PCa group compared to the disease control group (all p < 0.05). Conversely, the level of IL-4, TNF-α, IL-1ß, IL-17A and IFN-α were lower in the PCa group compared to those in control group. Following surgery, the concentration of IL-6 decreased; whereas, the concentrations of IL-4, TNF-α, IL-17A, IL-1ß, IL-12p70, and IFN-α increased, demonstrating significant differences (p < 0.05). The differential upregulation of IL-6 or downregulation of IL-17A in peripheral blood exhibited diagnostic efficacy in PCa patients. Moreover, we observed a significant increase in IL-17A levels, accompanied by decreased of IL-2, IL-4, IL-10, TNF-a, IFN-γ, IL-1ß, and IL-12P70 in patients with distant metastasis. CONCLUSION: The peripheral blood cytokines are closely associated with the occurrence and development of prostate cancer, especially the serum levels of IL-6 and IL-17A may be useful as potential predictors of PCa diagnosis.

Access to Prostate-Specific Antigen Testing and Mortality Among Men With Prostate Cancer.

Importance: Prostate-specific antigen (PSA) screening for prostate cancer is controversial but may be associated with benefit for certain high-risk groups. Objectives: To evaluate associations of county-level PSA screening prevalence with prostate cancer outcomes, as well as variation by sociodemographic and clinical factors. Design, Setting, and Participants: This cohort study used data from cancer registries based in 8 US states on Hispanic, non-Hispanic Black, and non-Hispanic White men aged 40 to 99 years who received a diagnosis of prostate cancer between January 1, 2000, and December 31, 2015. Participants were followed up until death or censored after 10 years or December 31, 2018, whichever end point came first. Data were analyzed between September 2023 and January 2024. Exposure: County-level PSA screening prevalence was estimated using the Behavior Risk Factor Surveillance System survey data from 2004, 2006, 2008, 2010, and 2012 and weighted by population characteristics. Main Outcomes and Measures: Multivariable logistic, Cox proportional hazards regression, and competing risks models were fit to estimate adjusted odds ratios (AOR) and adjusted hazard ratios (AHR) for associations of county-level PSA screening prevalence at diagnosis with advanced stage (regional or distant), as well as all-cause and prostate cancer-specific survival. Results: Of 814 987 men with prostate cancer, the mean (SD) age was 67.3 (9.8) years, 7.8% were Hispanic, 12.2% were non-Hispanic Black, and 80.0% were non-Hispanic White; 17.0% had advanced disease. There were 247 570 deaths over 5 716 703 person-years of follow-up. Men in the highest compared with lowest quintile of county-level PSA screening prevalence at diagnosis had lower odds of advanced vs localized stage (AOR, 0.86; 95% CI, 0.85-0.88), lower all-cause mortality (AHR, 0.86; 95% CI, 0.85-0.87), and lower prostate cancer-specific mortality (AHR, 0.83; 95% CI, 0.81-0.85). Inverse associations between PSA screening prevalence and advanced cancer were strongest among men of Hispanic ethnicity vs other ethnicities (AOR, 0.82; 95% CI, 0.78-0.87), older vs younger men (aged ≥70 years: AOR, 0.77; 95% CI, 0.75-0.79), and those in the Northeast vs other US Census regions (AOR, 0.81; 95% CI, 0.79-0.84). Inverse associations with all-cause mortality were strongest among men of Hispanic ethnicity vs other ethnicities (AHR, 0.82; 95% CI, 0.78-0.85), younger vs older men (AHR, 0.81; 95% CI, 0.77-0.85), those with advanced vs localized disease (AHR, 0.80; 95% CI, 0.78-0.82), and those in the West vs other US Census regions (AHR, 0.89; 95% CI, 0.87-0.90). Conclusions and Relevance: This population-based cohort study of men with prostate cancer suggests that higher county-level prevalence of PSA screening was associated with lower odds of advanced disease, all-cause mortality, and prostate cancer-specific mortality. Associations varied by age, race and ethnicity, and US Census region.