Abstract Context This review focuses on risk assessment and prediction tools for bladder cancer (BCa). Objective To review the current knowledge on risk assessment and prediction tools to enhance ...clinical decision making and counseling of patients with BCa. Evidence acquisition A literature search in English was performed using PubMed in July 2013. Relevant risk assessment and prediction tools for BCa were selected. More than 1600 publications were retrieved. Special attention was given to studies that investigated the clinical benefit of a prediction tool. Evidence synthesis Most prediction tools for BCa focus on the prediction of disease recurrence and progression in non–muscle-invasive bladder cancer or disease recurrence and survival after radical cystectomy. Although these tools are helpful, recent prediction tools aim to address a specific clinical problem, such as the prediction of organ-confined disease and lymph node metastasis to help identify patients who might benefit from neoadjuvant chemotherapy. Although a large number of prediction tools have been reported in recent years, many of them lack external validation. Few studies have investigated the clinical utility of any given model as measured by its ability to improve clinical decision making. There is a need for novel biomarkers to improve the accuracy and utility of prediction tools for BCa. Conclusions Decision tools hold the promise of facilitating the shared decision process, potentially improving clinical outcomes for BCa patients. Prediction models need external validation and assessment of clinical utility before they can be incorporated into routine clinical care. Patient summary We looked at models that aim to predict outcomes for patients with bladder cancer (BCa). We found a large number of prediction models that hold the promise of facilitating treatment decisions for patients with BCa. However, many models are missing confirmation in a different patient cohort, and only a few studies have tested the clinical utility of any given model as measured by its ability to improve clinical decision making.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Take-home message Many papers published in the urology literature have statistical errors. We present a set of guidelines for statistical analysis, reporting and interpretation. Appropriate adherence ...to these guidelines should help improve the quality of statistics in clinical urology research.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Spiritual well-being and sense of meaning are important concerns for clinicians who care for patients with cancer. We developed Individual Meaning-Centered Psychotherapy (IMCP) to address the need ...for brief interventions targeting spiritual well-being and meaning for patients with advanced cancer.
Patients with stage III or IV cancer (N = 120) were randomly assigned to seven sessions of either IMCP or therapeutic massage (TM). Patients were assessed before and after completing the intervention and 2 months postintervention. Primary outcome measures assessed spiritual well-being and quality of life; secondary outcomes included anxiety, depression, hopelessness, symptom burden, and symptom-related distress.
Of the 120 participants randomly assigned, 78 (65%) completed the post-treatment assessment and 67 (56%) completed the 2-month follow-up. At the post-treatment assessment, IMCP participants demonstrated significantly greater improvement than the control condition for the primary outcomes of spiritual well-being (b = 0.39; P <.001, including both components of spiritual well-being (sense of meaning: b = 0.34; P = .003 and faith: b = 0.42; P = .03), and quality of life (b = 0.76; P = .013). Significantly greater improvements for IMCP patients were also observed for the secondary outcomes of symptom burden (b = -6.56; P < .001) and symptom-related distress (b = -0.47; P < .001) but not for anxiety, depression, or hopelessness. At the 2-month follow-up assessment, the improvements observed for the IMCP group were no longer significantly greater than those observed for the TM group.
IMCP has clear short-term benefits for spiritual suffering and quality of life in patients with advanced cancer. Clinicians working with patients who have advanced cancer should consider IMCP as an approach to enhance quality of life and spiritual well-being.
Many randomized trials involve measuring a continuous outcome - such as pain, body weight or blood pressure - at baseline and after treatment. In this paper, I compare four possibilities for how such ...trials can be analyzed: post-treatment; change between baseline and post-treatment; percentage change between baseline and post-treatment and analysis of covariance (ANCOVA) with baseline score as a covariate. The statistical power of each method was determined for a hypothetical randomized trial under a range of correlations between baseline and post-treatment scores.
ANCOVA has the highest statistical power. Change from baseline has acceptable power when correlation between baseline and post-treatment scores is high;when correlation is low, analyzing only post-treatment scores has reasonable power. Percentage change from baseline has the lowest statistical power and was highly sensitive to changes in variance. Theoretical considerations suggest that percentage change from baseline will also fail to protect from bias in the case of baseline imbalance and will lead to an excess of trials with non-normally distributed outcome data.
Percentage change from baseline should not be used in statistical analysis. Trialists wishing to report this statistic should use another method, such as ANCOVA, and convert the results to a percentage change by using mean baseline scores.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Background. Decision curve analysis (DCA) is a widely used methodology in clinical research studies. Purpose. We performed a literature review to identify common errors in the application of DCA and ...provide practical suggestions for appropriate use of DCA. Data Sources. We first conducted an informal literature review and identified 6 errors found in some DCAs. We then used Google Scholar to conduct a systematic review of studies applying DCA to evaluate a predictive model, marker, or test. Data Extraction. We used a standard data collection form to collect data for each reviewed article. Data Synthesis. Each article was assessed according to the 6 predefined criteria for a proper analysis, reporting, and interpretation of DCA. Overall, 50 articles were included in the review: 54% did not select an appropriate range of probability thresholds for the x-axis of the DCA, with a similar proportion (50%) failing to present smoothed curves. Among studies with internal validation of a predictive model and correction for overfit, 61% did not clearly report whether the DCA had also been corrected. However, almost all studies correctly interpreted the DCA, used a correct outcome (92% for both), and clearly reported the clinical decision at issue (81%). Limitations. A comprehensive assessment of all DCAs was not performed. However, such a strategy would not influence the main findings. Conclusions. Despite some common errors in the application of DCA, our finding that almost all studies correctly interpreted the DCA results demonstrates that it is a clear and intuitive method to assess clinical utility.
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NUK, OILJ, SAZU, UKNU, UL, UM, UPUK, VSZLJ
Abstract Background The four-kallikrein panel and the Prostate Health Index (PHI) have been shown to improve prediction of prostate cancer (PCa) compared with prostate-specific antigen (PSA). No ...comparison of the four-kallikrein panel and PHI has been presented. Objective To compare the four-kallikrein panel and PHI for predicting PCa in an independent cohort. Design, setting, and participants Participants were from a population-based cohort of PSA-tested men in Stockholm County. We included 531 men with PSA levels between 3 and 15 ng/ml undergoing first-time prostate biopsy during 2010–2012. Outcome measurements and statistical analysis Models were fitted to case status. We computed calibration curves, the area under the receiver-operating characteristics curve (AUC), decision curves, and percentage of saved biopsies. Results and limitations The four-kallikrein panel showed AUCs of 69.0 when predicting any-grade PCa and 71.8 when predicting high-grade cancer (Gleason score ≥7). Similar values were found for PHI: 70.4 and 71.1, respectively. Both models had higher AUCs than a base model with PSA value and age ( p < 0.0001 for both); differences between models were not significant. Sensitivity analyses including men with any PSA level or a previous biopsy did not materially affect our findings. Using 10% predicted risk of high-grade PCa by the four-kallikrein panel or PHI of 39 as cut-off for biopsy saved 29% of performed biopsies at a cost of delayed diagnosis for 10% of the men with high-grade cancers. Both models showed limited net benefit in decision analysis. The main study limitation was lack of digital rectal examination data and biopsy decision being based on PSA information. Conclusions The four-kallikrein panel and PHI similarly improved discrimination when predicting PCa and high-grade PCa. Both are simple blood tests that can reduce the number of unnecessary biopsies compared with screening with total PSA, representing an important new option to reduce harm. Patient summary Prostate-specific antigen screening is controversial due to limitations of the test. We found that two blood tests, the Prostate Health Index and the four-kallikrein panel, performed similarly and could both aid in decision making among Swedish men undergoing a prostate biopsy.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
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