Dataset Information

A Nomogram Derived by Combination of Demographic and Biomarker Data Improves the Noninvasive Evaluation of Patients at Risk for Bladder Cancer.

ABSTRACT: Improvements in the noninvasive clinical evaluation of patients at risk for bladder cancer would be of benefit both to individuals and to health care systems. We investigated the potential utility of a hybrid nomogram that combined key demographic features with the results of a multiplex urinary biomarker assay in hopes of identifying patients at risk of harboring bladder cancer.Logistic regression analysis was used to model the probability of bladder cancer burden in a cohort of 686 subjects (394 with bladder cancer) using key demographic features alone, biomarker data alone, and the combination of demographic features and key biomarker data. We examined discrimination, calibration, and decision curve analysis techniques to evaluate prediction model performance.Area under the receiver operating characteristic curve (AUC) analyses revealed that demographic features alone predicted tumor burden with an accuracy of 0.806 [95% confidence interval (CI), 0.76-0.85], while biomarker data had an accuracy of 0.835 (95% CI, 0.80-0.87). The addition of molecular data into the nomogram improved the predictive performance to 0.891 (95% CI, 0.86-0.92). Decision curve analyses showed that the hybrid nomogram performed better than demographic or biomarker data alone.A nomogram construction strategy that combines key demographic features with biomarker data may facilitate the accurate, noninvasive evaluation of patients at risk of harboring bladder cancer. Further research is needed to evaluate the bladder cancer risk nomogram for potential clinical utility.The application of such a nomogram may better inform the decision to perform invasive diagnostic procedures. Cancer Epidemiol Biomarkers Prev; 25(9); 1361-6. ©2016 AACR.

SUBMITTER: Huang S

PROVIDER: S-EPMC5106243 | biostudies-literature | 2016 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A Nomogram Derived by Combination of Demographic and Biomarker Data Improves the Noninvasive Evaluation of Patients at Risk for Bladder Cancer.

Huang Sijia S Kou Lei L Furuya Hideki H Yu Changhong C Goodison Steve S Kattan Michael W MW Garmire Lana L Rosser Charles J CJ

Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology 20160706 9

<h4>Background</h4>Improvements in the noninvasive clinical evaluation of patients at risk for bladder cancer would be of benefit both to individuals and to health care systems. We investigated the potential utility of a hybrid nomogram that combined key demographic features with the results of a multiplex urinary biomarker assay in hopes of identifying patients at risk of harboring bladder cancer.<h4>Methods</h4>Logistic regression analysis was used to model the probability of bladder cancer bu ...[more]

PMID: 27383773

Similar Datasets

Project description:Purpose: Determine if gene expression profiles in urine sediment could provide non-invasive candidate markers for painful bladder syndrome (PBS) with and/or without Hunner lesions. Materials and Methods: Fresh catheterized urine was collected and centrifuged from control (n = 5), lesion-free (n = 5), and Hunner lesion bearing (n = 3) patients. RNA was extracted from the pelleted material and quantified by gene expression microarray (Affymetrix Human Gene ST Array). Results: Three biologically likely hypotheses were tested: A) all three groups are distinct from one another; B) controls are distinct from both types of PBS patients combined, and C) Hunner lesion PBS patients are distinct from controls and non-Hunner-lesion PBS combined. For statistical parity an unlikely fourth hypothesis was included: non-Hunner-lesion PBS patients are distinct from controls and Hunner lesion PBS combined. Analyses supported selective upregulation of genes in the Hunner lesion PBS group (hypothesis C), and these were primarily associated with inflammatory function. This profile is similar to that reported in a prior microarray study of bladder biopsies in Hunner lesion PBS. Conclusions: Urine sediment gene expression from non-Hunner-lesion PBS patients lacked a clear difference from that of control subjects, while the array signatures from PBS patients with Hunner lesions showed a clear, primarily inflammatory, signature. This signature was highly similar to that seen in a prior microarray study of bladder biopsies. Thus, although sample sizes were small, this work suggests that gene expression in urine sediment may provide a non-invasive biomarker for Hunner lesion, but not non-Hunner lesion, PBS. Urine (40-100 ml) was immediately placed on ice, transported to the laboratory and centrifuged at -4C for 5 minutes. Pellets were washed twice with ice-cold phosphate-buffered saline, suspended in 0.8 ml TRIzol and RNA was extracted according to the manufacturer's instructions. RNA was stored at -80oC until all samples had been collected, then analyzed at our Microarray Core Facility using the Affymetrix GeneChip Whole Transcript (WT) Sense Target Labeling Assay protocol, added to Human Gene 1.0 ST array chips, and annotated with gene symbol and functional information (Affymetrix). Probe level data were produced by Partek GS (6.10) using the gcRMA output option. Probe set signal intensities < 4.2 were considered absent, and if > 10 chips rated a probe set absent, that probe set was not considered for further analysis. Additionally, probe sets that did not have a gene symbol-level annotation (e.g., were considered 'hypothetical', or 'expressed sequence tags') were not considered for further analysis.

Project description:ObjectiveTo compare bladder sensitivity between patients with pelvic pain and patients who were pain free, undergoing noninvasive, controlled bladder distension via diuresis. We also sought to measure potential mechanisms underlying bladder sensitivity.DesignProspective observational study.SettingCommunity teaching hospital.PopulationReproductive-age women with non-bladder chronic pelvic pain (CPP, n = 23), painful bladder syndrome (PBS, n = 23), and pelvic pain-free controls (n = 42) METHODS: Participants were compared on cystometric capacity, pelvic floor pressure-pain thresholds (PPTs), pelvic muscle function, O'Leary-Sant bladder questionnaire, and psychosocial instruments using Wilcoxon rank-sum tests. Multivariate regression was used to identify factors underlying bladder pain phenotypes.Main outcome measuresPelvic floor pain thresholds; self-reported bladder distension pain.ResultsParticipants with PBS exhibited higher bladder distension pain than those with CPP, with both groups reporting higher pain levels than controls (P < 0.05). No significant associations were found between bladder distension pain and pelvic muscle structure or pain sensitivity measures; however, bladder distension pain positively correlates with both vaginal PPTs adjacent to the bladder (r = 0.46) and pain with transvaginal bladder palpation (r = 0.56). Pain at maximal distension was less influenced by somatic sensitivity than bladder symptoms (r = 0.35 versus r = 0.59; P < 0.05). Multivariate regression identified three independent components of bladder symptoms in PBS: bladder distension pain, bladder sensation, and somatic symptoms.ConclusionsDiuresis-induced bladder pain differentiates CPP from PBS. Experimental bladder pain is not predicted by pelvic floor sensitivity. Compared with patient-reported outcomes it appears less influenced by psychological factors. Further study is needed to determine whether screening for experimental bladder pain sensitivity could predict future risk of PBS.Tweetable abstractControlled, water ingestion-provoked bladder pain can objectively identify visceral pain sensitivity.

Dataset Information

A Nomogram Derived by Combination of Demographic and Biomarker Data Improves the Noninvasive Evaluation of Patients at Risk for Bladder Cancer.

Publications

A Nomogram Derived by Combination of Demographic and Biomarker Data Improves the Noninvasive Evaluation of Patients at Risk for Bladder Cancer.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets