Associations between depressive symptoms and disease progression in older patients with chronic kidney disease: results of the EQUAL study

Background Depressive symptoms are associated with adverse clinical outcomes in patients with end-stage kidney disease; however, few small studies have examined this association in patients with earlier phases of chronic kidney disease (CKD). We studied associations between baseline depressive symptoms and clinical outcomes in older patients with advanced CKD and examined whether these associations differed depending on sex. Methods CKD patients (>= 65 years; estimated glomerular filtration rate <= 20 mL/min/1.73 m(2)) were included from a European multicentre prospective cohort between 2012 and 2019. Depressive symptoms were measured by the five-item Mental Health Inventory (cut-off <= 70; 0-100 scale). Cox proportional hazard analysis was used to study associations between depressive symptoms and time to dialysis initiation, all-cause mortality and these outcomes combined. A joint model was used to study the association between depressive symptoms and kidney function over time. Analyses were adjusted for potential baseline confounders. Results Overall kidney function decline in 1326 patients was -0.12 mL/min/1.73 m(2)/month. A total of 515 patients showed depressive symptoms. No significant association was found between depressive symptoms and kidney function over time (P = 0.08). Unlike women, men with depressive symptoms had an increased mortality rate compared with those without symptoms [adjusted hazard ratio 1.41 (95% confidence interval 1.03-1.93)]. Depressive symptoms were not significantly associated with a higher hazard of dialysis initiation, or with the combined outcome (i.e. dialysis initiation and all-cause mortality). Conclusions There was no significant association between depressive symptoms at baseline and decline in kidney function over time in older patients with advanced CKD. Depressive symptoms at baseline were associated with a higher mortality rate in men

A Novel MiRNA-Based Predictive Model for Biochemical Failure Following Post-Prostatectomy Salvage Radiation Therapy

<div><p>Purpose</p><p>To develop a microRNA (miRNA)-based predictive model for prostate cancer patients of 1) time to biochemical recurrence after radical prostatectomy and 2) biochemical recurrence after salvage radiation therapy following documented biochemical disease progression post-radical prostatectomy.</p><p>Methods</p><p>Forty three patients who had undergone salvage radiation therapy following biochemical failure after radical prostatectomy with greater than 4 years of follow-up data were identified. Formalin-fixed, paraffin-embedded tissue blocks were collected for all patients and total RNA was isolated from 1mm cores enriched for tumor (>70%). Eight hundred miRNAs were analyzed simultaneously using the nCounter human miRNA v2 assay (NanoString Technologies; Seattle, WA). Univariate and multivariate Cox proportion hazards regression models as well as receiver operating characteristics were used to identify statistically significant miRNAs that were predictive of biochemical recurrence.</p><p>Results</p><p>Eighty eight miRNAs were identified to be significantly (p<0.05) associated with biochemical failure post-prostatectomy by multivariate analysis and clustered into two groups that correlated with early (≤ 36 months) versus late recurrence (>36 months). Nine miRNAs were identified to be significantly (p<0.05) associated by multivariate analysis with biochemical failure after salvage radiation therapy. A new predictive model for biochemical recurrence after salvage radiation therapy was developed; this model consisted of miR-4516 and miR-601 together with, Gleason score, and lymph node status. The area under the ROC curve (AUC) was improved to 0.83 compared to that of 0.66 for Gleason score and lymph node status alone.</p><p>Conclusion</p><p>miRNA signatures can distinguish patients who fail soon after radical prostatectomy versus late failures, giving insight into which patients may need adjuvant therapy. Notably, two novel miRNAs (miR-4516 and miR-601) were identified that significantly improve prediction of biochemical failure post-salvage radiation therapy compared to clinico-histopathological factors, supporting the use of miRNAs within clinically used predictive models. Both findings warrant further validation studies.</p></div

Univariate analysis for molecular and clinical variables.

<p>Univariate log-rank tests were performed using the newly identified 88-miRNA cluster of failure post-RP and the newly developed predictive salvage radiation therapy (RT) model as well as several clinical factors to determine the ability of each factor to predict time to failure post-radical prostatectomy (RP) and failure post-salvage RT. Prostate specific antigen (PSA) and age were treated as continuous variables whereas other clinical factors were categorized as follows: Gleason score: 6, 7, and ≥8; lymph node: positive or negative; positive surgical margins: R0, R1 and Rx; pathological T stage: (T2, T2a, and T2b), (T2c), and (T3a and T3b); D’Amico risk classification: high and intermediate; Stephensen risk classification: high plus, high, intermediate, and low. n/a, not applicable.</p><p>Univariate analysis for molecular and clinical variables.</p

miRNAs that correlate with biochemical recurrence after salvage radiation in PCa patients.

<p>Hazards ratios were generated using a multivariate Cox regression analysis (lymph node status and Gleason score). Literature supporting their role(s) in prostate cancer (PCa) as well as other cancers are referenced. Bolded are those miRNAs that are novel to PCa. Only miRNAs with a significant p-value (<0.05) are shown. CI, confidence interval</p><p>miRNAs that correlate with biochemical recurrence after salvage radiation in PCa patients.</p

Clinical characteristics of 43 prostate cancer patients treated with salvage radiation therapy post-prostatectomy.

<p>RP, radical prostatectomy; min, minimum; max, maximum; RT, radiation therapy; op, operation; PSA, prostate-specific antigen.</p><p>Clinical characteristics of 43 prostate cancer patients treated with salvage radiation therapy post-prostatectomy.</p

Area under the receiver operating characteristic curve (AUC) of miRNA-based predictive salvage RT model.

<p>AUC curves were generated using a stepwise Cox regression model to determine a signature predictive of biochemical recurrence post-salvage radiation therapy. Gleason score, lymph node status, hsa-miR-4516, and hsa-miR-601 (red) performs the best with an AUC of 0.83 followed by a model containing hsa-miR-601-alone (green) (AUC = 0.77), hsa-miR-4516-alone (blue) (AUC = 0.68), and lastly, Gleason score and lymph node status (grey) (AUC = 0.66).</p

Study design.

<p>All patients underwent radical prostatectomy and salvage radiation therapy following biochemical recurrence. Tissue isolated at the time of radical prostatectomy (n = 43) was used for miRNA profiling.</p

88-miRNA signature predicts early vs late biochemical recurrence post-RP.

<p>Cluster analysis was performed using the statistically significant 88 miRNAs predictive of first biochemical recurrence using Cox regression multivariable analysis (D’Amico score, Stephensen score (categorical), and Stephensen score (continuous)). This signature (A) appears to differentiate between patients with early recurrence (< 36 months) (red box) vs those with late recurrence (> 36 months). Kaplan-Meier plots were generated using the two cluster groups (B). Cluster 1 (blue), left cluster/early recurrence group; Cluster 2 (red), right cluster/late recurrence group.</p

Kaplan-Meier plot estimates of miRNA-based predictive salvage RT model.

<p>A K-M plot was generated using the miR-4516 + miR-601 + Gleason score + lymph node status model for biochemical recurrence post salvage radiation therapy. Patients were divided into high and low risk groups dichotomized by the median risk score.</p