CMDX©-based single source information system for simplified quality management and clinical research in prostate cancer

Background: Histopathological evaluation of prostatectomy specimens is crucial to decision-making and prediction of patient outcomes in prostate cancer (PCa). Topographical information regarding PCa extension and positive surgical margins (PSM) is essential for clinical routines, quality assessment, and research. However, local hospital information systems (HIS) often do not support the documentation of such information. Therefore, we investigated the feasibility of integrating a cMDX-based pathology report including topographical information into the clinical routine with the aims of obtaining data, performing analysis and generating heat maps in a timely manner, while avoiding data redundancy. Methods: We analyzed the workflow of the histopathological evaluation documentation process. We then developed a concept for a pathology report based on a cMDX data model facilitating the topographical documentation of PCa and PSM; the cMDX SSIS is implemented within the HIS of University Hospital Muenster. We then generated a heat map of PCa extension and PSM using the data. Data quality was assessed by measuring the data completeness of reports for all cases, as well as the source-to-database error. We also conducted a prospective study to compare our proposed method with recent retrospective and paper-based studies according to the time required for data analysis. Results: We identified 30 input fields that were applied to the cMDX-based data model and the electronic report was integrated into the clinical workflow. Between 2010 and 2011, a total of 259 reports were generated with 100% data completeness and a source-to-database error of 10.3 per 10,000 fields. These reports were directly reused for data analysis, and a heat map based on the data was generated. PCa was mostly localized in the peripheral zone of the prostate. The mean relative tumor volume was 16.6%. The most PSM were localized in the apical region of the prostate. In the retrospective study, 1623 paper-based reports were transferred to cMDX reports; this process took 15 ± 2 minutes per report. In a paper-based study, the analysis data preparation required 45 ± 5 minutes per report. Conclusions: cMDX SSIS can be integrated into the local HIS and provides clinical routine data and timely heat maps for quality assessment and research purposes.

Clinical map document based on XML (cMDX): document architecture with mapping feature for reporting and analysing prostate cancer in radical prostatectomy specimens

<p>Abstract</p> <p>Background</p> <p>The pathology report of radical prostatectomy specimens plays an important role in clinical decisions and the prognostic evaluation in Prostate Cancer (PCa). The anatomical schema is a helpful tool to document PCa extension for clinical and research purposes. To achieve electronic documentation and analysis, an appropriate documentation model for anatomical schemas is needed. For this purpose we developed cMDX.</p> <p>Methods</p> <p>The document architecture of cMDX was designed according to Open Packaging Conventions by separating the whole data into template data and patient data. Analogue custom XML elements were considered to harmonize the graphical representation (e.g. tumour extension) with the textual data (e.g. histological patterns). The graphical documentation was based on the four-layer visualization model that forms the interaction between different custom XML elements. Sensible personal data were encrypted with a 256-bit cryptographic algorithm to avoid misuse. In order to assess the clinical value, we retrospectively analysed the tumour extension in 255 patients after radical prostatectomy.</p> <p>Results</p> <p>The pathology report with cMDX can represent pathological findings of the prostate in schematic styles. Such reports can be integrated into the hospital information system. "cMDX" documents can be converted into different data formats like text, graphics and PDF. Supplementary tools like cMDX Editor and an analyser tool were implemented. The graphical analysis of 255 prostatectomy specimens showed that PCa were mostly localized in the peripheral zone (Mean: 73% ± 25). 54% of PCa showed a multifocal growth pattern.</p> <p>Conclusions</p> <p>cMDX can be used for routine histopathological reporting of radical prostatectomy specimens and provide data for scientific analysis.</p

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The presence of positive surgical margins in patients with organ-confined prostate cancer results in biochemical recurrence at a similar rate to that in patients with extracapsular extension and PSA <= 10 ng/ml

Purposes: We investigated whether patients with organ-confined prostate cancer (PCa) and positive surgical margins (SMs) had a similar biochemical recurrence (BCR) risk compared with patients with pT3a and preoperative prostate-specific antigen (PSA) levels 10 ng/ml and pT3b. Men with pT2R1 had a shorter time to BCR compared with men with pT3a-PSA = 7a was correlated with a poorer BCR rate than GIs pT2R1/pT3a-PSA > 10 ng/ml > pT2R1/pT3a PSA pT2R0 (P = 7b is associated with a high BCR risk in these patient groups. Including SM status, PSA, and GIs in pT stage appears to improve prognostic stratification in patients with PCa. (C) 2014 Elsevier Inc. All rights reserved

Tumor percentage but not number of tumor foci predicts disease-free survival after radical prostatectomy especially in high-risk patients

Objective: To evaluate the predictive value of tumor volume (TV), tumor percentage (TP), and number of tumor foci (NF) in patients with prostate cancer. The prognostic relevance of TV, TP, and NF as predictors of biochemical recurrence (BCR) following radical prostatectomy (RPE) is controversial. Patients and methods: The cohort consisted of 758 referred subjects who underwent RPE between 2000 and 2005 at the University of Muenster. The mean time of follow-up was 62 months. TV, TP, and NF were estimated visually with the assistance of a pathologic mapping grid for embedded whole-mount RPE specimens. In addition, TV and TP were assessed in a categorized fashion by using quartiles as cutoff points. Subgroup analyses for high- and low-risk patients using univariate and multivariate Cox proportional hazard analyses for BCR were performed. Results: TV, TP, and NF were strongly related to tumor stage, Gleason score, surgical margin status, and preoperative prostate-specific antigen (PSA). In univariate analysis, all pathologic parameters including TV, TP, and NF were predictive for BCR. In multivariate analysis, only TP, tumor stage, and PSA level were independent predictors. In subgroup analysis, TP was an independent predictor for BCR in the high-risk group but not in the low-risk group. Conclusions: TP, but not TV or NF, was found to be an independent predictor for BCR in patients after RPE, TP seems to be more relevant in high-risk patients (i.e., any of the following: >pT2, Gleason score >6, or PSA >20 ng/ml). (C) 2014 Elsevier Inc. All rights reserved

CMDX (c)-based single source information system for simplified quality management and clinical research in prostate cancer

Background: Histopathological evaluation of prostatectomy specimens is crucial to decision-making and prediction of patient outcomes in prostate cancer (PCa). Topographical information regarding PCa extension and positive surgical margins (PSM) is essential for clinical routines, quality assessment, and research. However, local hospital information systems (HIS) often do not support the documentation of such information. Therefore, we investigated the feasibility of integrating a cMDX-based pathology report including topographical information into the clinical routine with the aims of obtaining data, performing analysis and generating heat maps in a timely manner, while avoiding data redundancy. Methods: We analyzed the workflow of the histopathological evaluation documentation process. We then developed a concept for a pathology report based on a cMDX data model facilitating the topographical documentation of PCa and PSM; the cMDX SSIS is implemented within the HIS of University Hospital Muenster. We then generated a heat map of PCa extension and PSM using the data. Data quality was assessed by measuring the data completeness of reports for all cases, as well as the source-to-database error. We also conducted a prospective study to compare our proposed method with recent retrospective and paper-based studies according to the time required for data analysis. Results: We identified 30 input fields that were applied to the cMDX-based data model and the electronic report was integrated into the clinical workflow. Between 2010 and 2011, a total of 259 reports were generated with 100% data completeness and a source-to-database error of 10.3 per 10,000 fields. These reports were directly reused for data analysis, and a heat map based on the data was generated. PCa was mostly localized in the peripheral zone of the prostate. The mean relative tumor volume was 16.6%. The most PSM were localized in the apical region of the prostate. In the retrospective study, 1623 paper-based reports were transferred to cMDX reports; this process took 15 +/- 2 minutes per report. In a paper-based study, the analysis data preparation required 45 +/- 5 minutes per report. Conclusions: cMDX SSIS can be integrated into the local HIS and provides clinical routine data and timely heat maps for quality assessment and research purposes

Preoperative Serum Prostate-Specific Antigen Levels Vary According to the Topographical Distribution of Prostate Cancer in Prostatectomy Specimens

OBJECTIVE To evaluate whether the spatial distribution of prostate cancer (PCa) influences the concentration of prostate-specific antigen (PSA). METHODS An observational prospective study was performed in 775 consecutive men with preoperative PSA levels <= 20 ng/mL who underwent radical prostatectomy for organ-confined PCa. We evaluated prostate specimens using a cMDX-based map model of the prostate and determined the prostate volume, number of cancer foci, relative tumor volume, Gleason score, zone of origin, localization, and pathologic stage after stratification according to PSA levels categorized into 3 groups: <4 ng/mL, 4-10 ng/mL, and 10.1-20 ng/mL. The distribution of 5254 PCa foci was analyzed after stratification according to PSA levels and visualized on heat maps. A logistic regression analysis was performed to assess the odds ratios of PSA levels for the presence of PCa in 16 regions. RESULTS PCa with PSA <4 ng/mL was predominantly localized to the apical part and the peripheral zone of the prostate. PCa with a PSA level 10.1-20 ng/mL (16.4% of cases) was observed more frequently in the anterior part and the base of the prostate than PCa with a PSA level <4 or 410 ng/mL (6% and 10%, respectively). CONCLUSION Preoperative PSA levels vary according to the spatial distribution of PCa in radical prostatectomy specimens. The probability of anterior PCa is increased with higher PSA serum levels. Regions of interest harboring the PCa can be defined according to preoperative PSA and prostate volume. These findings are useful to optimize the focal therapy or to adjust the radiation fields. (C) 2015 Elsevier Inc

CMDX©-based single source information system for simplified quality management and clinical research in prostate cancer

Abstract Background Histopathological evaluation of prostatectomy specimens is crucial to decision-making and prediction of patient outcomes in prostate cancer (PCa). Topographical information regarding PCa extension and positive surgical margins (PSM) is essential for clinical routines, quality assessment, and research. However, local hospital information systems (HIS) often do not support the documentation of such information. Therefore, we investigated the feasibility of integrating a cMDX-based pathology report including topographical information into the clinical routine with the aims of obtaining data, performing analysis and generating heat maps in a timely manner, while avoiding data redundancy. Methods We analyzed the workflow of the histopathological evaluation documentation process. We then developed a concept for a pathology report based on a cMDX data model facilitating the topographical documentation of PCa and PSM; the cMDX SSIS is implemented within the HIS of University Hospital Muenster. We then generated a heat map of PCa extension and PSM using the data. Data quality was assessed by measuring the data completeness of reports for all cases, as well as the source-to-database error. We also conducted a prospective study to compare our proposed method with recent retrospective and paper-based studies according to the time required for data analysis. Results We identified 30 input fields that were applied to the cMDX-based data model and the electronic report was integrated into the clinical workflow. Between 2010 and 2011, a total of 259 reports were generated with 100% data completeness and a source-to-database error of 10.3 per 10,000 fields. These reports were directly reused for data analysis, and a heat map based on the data was generated. PCa was mostly localized in the peripheral zone of the prostate. The mean relative tumor volume was 16.6%. The most PSM were localized in the apical region of the prostate. In the retrospective study, 1623 paper-based reports were transferred to cMDX reports; this process took 15 ± 2 minutes per report. In a paper-based study, the analysis data preparation required 45 ± 5 minutes per report. Conclusions cMDX SSIS can be integrated into the local HIS and provides clinical routine data and timely heat maps for quality assessment and research purposes.</p

Preoperative prostate-specific antigen isofonn p2PSA <= 22.5 pg/ml predicts advanced prostate cancer in patients undergoing radical prostatectomy

Background: The prediction value of prostate-specific antigen (PSA) isoform [-2]proPSA (p2PSA) for detecting advanced prostate cancer (PCa) remains unclear. Our objective was to evaluate the additional clinical utility of p2PSA compared with total PSA (tPSA), free PSA (fPSA), and preoperative Gleason score (GIs) in predicting locally advanced PCa (pT3/T4) with high-accuracy discrimination The aim was to develop a novel classification based on p2PSA and preoperative GIs for predicting advanced PCa. Materials and methods: In 208 consecutive men diagnosed with clinically localized PCa who underwent radical prostatectomy, we determined the predictive and discriminatory accuracy of serum tPSA, fPSA, percentage of fPSA to tPSA, p2PSA, p2PSA density, percentage of p2PSA to fPSA, and the Prostate Health Index. The cutoff level of p2PSA with best accuracy was estimated. The novel classification was developed by analyzing the interaction between p2PSA and Gls in predicting pathologic outcomes using a chi-square automatic interaction detection analysis. Decision curve analysis was applied to test the clinical consequences of using the novel classification. Results: On univariate analyses, p2PSA, p2PSA density, percentage of p2PSA to fPSA, and Prostate Health Index were accurate but were not independent predictors by multivariate analysis. The p2PSA cutoff level of 22.5 pg/ml showed the best accuracy level for predicting and discriminating advanced diseases (area under the curve [AUC] = 0.725, sensitivity = 51.4%, specificity = 81.8%). By chisquare automatic interaction detection, univariate and multivariate analysis, a p2PSA level >22.5 pg/ml was significantly associated with an increased frequency and risk of advanced disease. In patients with a p2PSA level 7a). (C) 2014 Elsevier Inc. All rights reserved

Blind Biobanking of the Prostatectomy Specimen: Critical Evaluation of the Existing Techniques and Development of the New 4-Level Tissue Extraction Model With High Sampling Efficacy

BACKGROUND. Fresh tissue is mandatory to perform high-quality translation studies. Several models for tissue extraction from prostatectomy specimens without guidance by frozen sections are already introduced. However, little is known about the sampling efficacy of these models, which should provide representative tissue in adequate volumes, account for multifocality and heterogeneity of tumor, not violate the routine final pathological examination, and perform quickly without frozen section-based histological control. The aim of the study was to evaluate the sampling efficacy of the existing tissue extraction models without guidance by frozen sections (blind) and to develop an optimized model for tissue extraction. METHODS. Five hundred thirty-three electronic maps of the tumor distribution in prostates from a single-center cohort of the patients subjected to radical prostatectomy were used for analysis. Six available models were evaluated in silico for their sampling efficacy. Additionally, a novel model achieving the best sampling efficacy was developed. RESULTS. The available models showed high efficacies for sampling any part from the tumor (up to 100%), but were uniformly low in efficacy to sample all tumor foci from the specimens (with the best technique sampling only 51.6% of the all tumor foci). The novel 4-level extraction model achieved a sampling efficacy of 93.1% for all tumor foci. CONCLUSIONS. The existing blind tissue extraction models from prostatectomy specimens without frozen sections control are suitable to target tumor tissues but these tissues do not represent the whole tumor. The novel 4-level model provides the highest sampling efficacy and a promising potential for integration into routine. (C) 2016 Wiley Periodicals, Inc