Positive predictive value of mpmri in men under active surveillance: Can the biopsy history influence radiological assessment?

Objective.Some policy makers have embraced public reporting of healthcare-associated infections (HAIs) as a strategy for improving patient safety and reducing healthcare costs. We compared the accuracy of 2 methods of identifying cases of HAI: review of administrative data and targeted active surveillance.Design, Setting, and Participants.A cross-sectional prospective study was performed during a 9-month period in 2004 at the Children's Hospital of Philadelphia, a 418-bed academic pediatric hospital. “True HAI” cases were defined as those that met the definitions of the National Nosocomial Infections Surveillance System and that were detected by a trained infection control professional on review of the medical record. We examined the sensitivity and the positive and negative predictive values of identifying HAI cases by review of administrative data and by targeted active surveillance.Results.We found similar sensitivities for identification of HAI cases by review of administrative data (61%) and by targeted active surveillance (76%). However, the positive predictive value of identifying HAI cases by review of administrative data was poor (20%), whereas that of targeted active surveillance was 100%.Conclusions.The positive predictive value of identifying HAI cases by targeted active surveillance is very high. Additional investigation is needed to define the optimal detection method for institutions that provide HAI data for comparative analysis.

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Simulated clinical deployment of fully automatic deep learning for clinical prostate MRI assessment

European Radiology ◽

10.1007/s00330-020-07086-z ◽

2020 ◽

Vol 31 (1) ◽

pp. 302-313

Author(s):

Patrick Schelb ◽

Xianfeng Wang ◽

Jan Philipp Radtke ◽

Manuel Wiesenfarth ◽

Philipp Kickingereder ◽

...

Keyword(s):

Quality Assurance ◽

Deep Learning ◽

Positive Predictive Value ◽

Predictive Value ◽

Learning Algorithm ◽

Simultaneous Detection ◽

Calibration Method ◽

Radiological Assessment ◽

Grade Group ◽

Predictive Values

Abstract Objectives To simulate clinical deployment, evaluate performance, and establish quality assurance of a deep learning algorithm (U-Net) for detection, localization, and segmentation of clinically significant prostate cancer (sPC), ISUP grade group ≥ 2, using bi-parametric MRI. Methods In 2017, 284 consecutive men in active surveillance, biopsy-naïve or pre-biopsied, received targeted and extended systematic MRI/transrectal US-fusion biopsy, after examination on a single MRI scanner (3 T). A prospective adjustment scheme was evaluated comparing the performance of the Prostate Imaging Reporting and Data System (PI-RADS) and U-Net using sensitivity, specificity, predictive values, and the Dice coefficient. Results In the 259 eligible men (median 64 [IQR 61–72] years), PI-RADS had a sensitivity of 98% [106/108]/84% [91/108] with a specificity of 17% [25/151]/58% [88/151], for thresholds at ≥ 3/≥ 4 respectively. U-Net using dynamic threshold adjustment had a sensitivity of 99% [107/108]/83% [90/108] (p > 0.99/> 0.99) with a specificity of 24% [36/151]/55% [83/151] (p > 0.99/> 0.99) for probability thresholds d3 and d4 emulating PI-RADS ≥ 3 and ≥ 4 decisions respectively, not statistically different from PI-RADS. Co-occurrence of a radiological PI-RADS ≥ 4 examination and U-Net ≥ d3 assessment significantly improved the positive predictive value from 59 to 63% (p = 0.03), on a per-patient basis. Conclusions U-Net has similar performance to PI-RADS in simulated continued clinical use. Regular quality assurance should be implemented to ensure desired performance. Key Points • U-Net maintained similar diagnostic performance compared to radiological assessment of PI-RADS ≥ 4 when applied in a simulated clinical deployment. • Application of our proposed prospective dynamic calibration method successfully adjusted U-Net performance within acceptable limits of the PI-RADS reference over time, while not being limited to PI-RADS as a reference. • Simultaneous detection by U-Net and radiological assessment significantly improved the positive predictive value on a per-patient and per-lesion basis, while the negative predictive value remained unchanged.

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Elastography Targeted Prostate Biopsy in Patients under Active Surveillance

Urologia Internationalis ◽

10.1159/000509256 ◽

2020 ◽

Vol 104 (11-12) ◽

pp. 948-953

Author(s):

Tobias Steinwender ◽

Lukas Manka ◽

Mircea Grindei ◽

Zhe Tian ◽

Alexander Winter ◽

...

Keyword(s):

Prostate Cancer ◽

Positive Predictive Value ◽

Active Surveillance ◽

Prostate Biopsy ◽

Predictive Value ◽

Individual Case ◽

Cancer Center ◽

Sensitivity Specificity ◽

Targeted Biopsies

Objective: The aim of this study was to examine elastography-based prostate biopsy in prostate cancer (PCa) patients under active surveillance. Patients and Methods: We relied on PCa patients who opted for active surveillance and underwent elastography targeted and systematic follow-up biopsy at the Braunschweig Prostate Cancer Center between October 2009 and February 2015. Each prostate sextant was considered as an individual case. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy (ACC) for elastography to predict follow-up biopsy results were analyzed, respectively, and 95 % confidence intervals (CIs) were carried out by using 2000 bootstrapping sample analyses. Results: Overall, 50 men and 300 sextants were identified. Overall, 27 (54%) men and 66 (22%) sextants harbored PCa at follow-up biopsy. Sensitivity, specificity, PPV, NPV, and ACC for elastography to predict follow-up biopsy results were: 19.7 (95% CI: 11.9–27.3), 86.8 (95% CI: 82.7–90.3), 29.6 (95% CI: 14.6–46.0), 79.3 (95% CI: 71.6–86.5), and 72.0% (95% CI: 65.7–78.3), respectively. Conclusions: We recorded limited reliability of elastography-based prediction of follow-up biopsy results in active surveillance patients. Based on our analyses, we can neither recommend to rely exclusively on elastography-based targeted biopsies nor to delay or to omit follow-up biopsies based on elastography results during active surveillance.

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Predictive value of endoscopic esophageal findings for residual esophageal cancer after neoadjuvant chemoradiotherapy

Endoscopy ◽

10.1055/a-1362-9375 ◽

2021 ◽

Author(s):

Ruben D. van der Bogt ◽

Berend J. van der Wilk ◽

Suzan Nikkessen ◽

Kausilia K. Krishnadath ◽

Erik J. Schoon ◽

...

Keyword(s):

Esophageal Cancer ◽

Positive Predictive Value ◽

Active Surveillance ◽

Predictive Value ◽

Residual Disease ◽

Neoadjuvant Chemoradiotherapy ◽

Residual Tumor ◽

Scar Tissue ◽

Endoscopic Findings ◽

Resection Specimen

Abstract Background Endoscopic evaluation of the esophageal mucosa may play a role in an active surveillance strategy after neoadjuvant chemoradiotherapy (nCRT) for esophageal cancer. This study investigated the yield of endoscopic findings for detection of residual disease. Methods Patients from the multicenter preSANO cohort, who underwent nCRT followed by surgery for esophageal or junctional cancer, were included. Upper endoscopy was performed 6 and 12 weeks after nCRT. Patients with residual disease at 6 weeks underwent immediate surgery. Endoscopic records were reviewed for presence of stenosis, suspicion of residual tumor, scar tissue, and ulceration. Presence and type of endoscopic findings were compared with outcome of the resection specimen. Results 118 of 156 patients (76 %) had residual disease in the resection specimen. Endoscopic suspicion of residual tumor was significantly associated with presence of residual disease. At 6 weeks, 40/112 patients with residual disease and 4/33 patients with complete response had endoscopic suspicion of residual tumor (36 % vs. 12 %; P = 0.01), while this was reported in 16/73 and 0/28 patients, respectively, at 12 weeks (22 % vs. 0 %; P < 0.01). Positive predictive value of endoscopic suspicion of residual tumor was 91 % at 6 weeks and 100 % at 12 weeks. Endoscopic findings of non-passable stenosis, passable stenosis, scar tissue, or ulceration were not associated with residual disease. Conclusions Endoscopic suspicion of residual tumor was the only endoscopic finding associated with residual disease. Based on its positive predictive value, this endoscopic finding may contribute to the diagnostic strategy used in active surveillance.

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Diagnosis of cerebral hemorrhage before the era of computed tomography

Orvosi Hetilap ◽

10.1556/oh.2013.29739 ◽

2013 ◽

Vol 154 (44) ◽

pp. 1743-1746

Author(s):

Gergely Hofgárt ◽

Rita Szepesi ◽

Bertalan Vámosi ◽

László Csiba

Keyword(s):

Computed Tomography ◽

Cerebrospinal Fluid ◽

Positive Predictive Value ◽

Predictive Value ◽

Hemorrhagic Stroke ◽

Cranial Computed Tomography ◽

Cerebral Stroke ◽

Daily Routine ◽

Stroke Patients ◽

The Difference

Introduction: During the past decades there has been a great progress in neuroimaging methods. Cranial computed tomography is part of the daily routine now and its use allows a fast diagnosis of parenchymal hemorrhage. However, before the availability of computed tomography the differentiation between ischemic and hemorrhagic stroke was based on patient history, physical examination, percutan angiography and cerebrospinal fluid sampling, and the clinical utility could be evaluated by autopsy of deceased patients. Aim: The authors explored the diagnostic performance of cerebrospinal fluid examination for the diagnosis of ischemic and hemorrhagic stroke. Method: Data of 200 deceased stroke patients were retrospectively evaluated. All patients had liquor sampling at admission and all of them had brain autopsy. Results: Bloody or yellowish cerebrospinal fluid at admission had a positive predictive value of 87.5% for hemorrhagic stroke confirmed by autopsy, while clear cerebrospinal fluid had positive predictive value of 90.7% for ischemic stroke. Patients who had clear liquor, but autopsy revealed hemorrhagic stroke had higher protein level in the cerebrospinal fluid, but the difference was not statistically significant (p = 0.09). Conclusions: The results confirm the importance of pathological evaluation of the brain in cases deceased from cerebral stroke. With this article the authors wanted to salute for those who contributed to the development of the Hungarian neuropathology. In this year we remember the 110th anniversary of the birth, and the 60th anniversary of the death of professor Kálmán Sántha. Professor László Molnár would be 90 years old in 2013. Orv. Hetil., 154 (44), 1743–1746.

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VALUE OF COMBINATION OF HAP SCORE AND BISAP SCORE IN PREDICTING SEVERITY IN PATIENTS OF ACUTE PANCREATITIS

Journal of Medicine and Pharmacy ◽

10.34071/jmp.2019.1.15 ◽

2019 ◽

pp. 96-100

Author(s):

Thi Ngoc Suong Le ◽

Pham Chi Tran ◽

Van Huy Tran

Keyword(s):

Acute Pancreatitis ◽

Positive Predictive Value ◽

Roc Curve ◽

Predictive Value ◽

Prognostic Value ◽

Acute Inflammation ◽

Clinical Symptoms ◽

Mortality Rates ◽

Multiple Organ ◽

Central Hospital

Acute pancreatitis (AP) is an acute inflammation of the pancreas, usually occurs suddenly with a variety of clinical symptoms, complications of multiple organ failure and high mortality rates. Objectives: To determine the value of combination of HAP score and BISAP score in predicting the severity of acute pancreatitis of the Atlanta 2012 Classification. Patients and Methods: 75 patients of acute pancreatitis hospitalized at Hue Central Hospital between March 2017 and July 2018; HAP and BISHAP score is calculated within the first 24 hours. The severity of AP was classified by the revised Atlanta criteria 2012. Results: When combining the HAP and BISAP scores in predicting the severity of acute pancreatitis, the area under the ROC curve was 0,923 with sensitivity value was 66.7%, specificity value was 97.1%; positive predictive value was 66.7%, negative predictive value was 97.1%. Conclusion: The combination of HAP and BISAP scores increased the sensitivity, predictive value, and prognostic value in predicting the severity of acute pancreatitis of the revised Atlanta 2012 classification in compare to each single scores. Key words: HAPscore, BiSAP score, acute pancreatitis, predicting severity

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Faculty Opinions recommendation of Positive predictive value estimates for cell-free noninvasive prenatal screening from data of a large referral genetic diagnostic laboratory.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.731997757.793559896 ◽

2019 ◽

Author(s):

Tomas Szemes

Keyword(s):

Positive Predictive Value ◽

Predictive Value ◽

Prenatal Screening ◽

Diagnostic Laboratory ◽

Noninvasive Prenatal Screening

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Accuracy of MSCT Coronary Angiography with 64 Row CT Scanner—Facing the Facts

Clinical Medicine Insights Cardiology ◽

10.4137/cmc.s3864 ◽

2010 ◽

Vol 4 ◽

pp. CMC.S3864 ◽

Cited By ~ 3

Author(s):

M. Wehrschuetz ◽

E. Wehrschuetz ◽

H. Schuchlenz ◽

G. Schaffler

Keyword(s):

Coronary Artery Disease ◽

Coronary Artery ◽

Coronary Angiography ◽

Positive Predictive Value ◽

Diagnostic Accuracy ◽

Predictive Value ◽

Diagnostic Potential ◽

Coronary Artery Stenoses ◽

Artery Disease ◽

Msct Angiography

Improvements in multislice computed tomography (MSCT) angiography of the coronary vessels have enabled the minimally invasive detection of coronary artery stenoses, while quantitative coronary angiography (QCA) is the accepted reference standard for evaluation thereof. Sixteen-slice MSCT showed promising diagnostic accuracy in detecting coronary artery stenoses haemodynamically and the subsequent introduction of 64-slice scanners promised excellent and fast results for coronary artery studies. This prompted us to evaluate the diagnostic accuracy, sensitivity, specificity, and the negative und positive predictive value of 64-slice MSCT in the detection of haemodynamically significant coronary artery stenoses. Thirty-seven consecutive subjects with suspected coronary artery disease were evaluated with MSCT angiography and the results compared with QCA. All vessels were considered for the assessment of significant coronary artery stenosis (diameter reduction ≥ 50%). Thirteen patients (35%) were identified as having significant coronary artery stenoses on QCA with 6.3% (35/555) affected segments. None of the coronary segments were excluded from analysis. Overall sensitivity for classifying stenoses of 64-slice MSCT was 69%, specificity was 92%, positive predictive value was 38% and negative predictive value was 98%. The interobserver variability for detection of significant lesions had a κ-value of 0.43. Sixty-four-slice MSCT offers the diagnostic potential to detect coronary artery disease, to quantify haemodynamically significant coronary artery stenoses and to avoid unnecessary invasive coronary artery examinations.

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