Do prostate cancer nomograms give accurate information when applied to European patients?

Turo, Rafal; Forster, James A.; West, Robert; Prescott, Stephen M.; Paul, Alan; Cross, William

doi:10.3109/21681805.2014.920415

Cited by 19 publications

(15 citation statements)

References 28 publications

(49 reference statements)

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…We also observed a clear unbalance towards sensitivity vs. specificity in the case of PT, and specificity vs. sensitivity in the case of MSKCCn and CAPRA, respectively. A possible explanation for our findings is that the results of clinical models depend on the population of application . This supports the idea that adding mpMRI can improve the models performance, given a more objective representation of cancer presence and extent.…”

Section: Discussionsupporting

confidence: 81%

“…A possible explanation for our findings is that the results of clinical models depend on the population of application. 12,21 This supports the idea that adding mpMRI can improve the models performance, given a more objective representation of cancer presence and extent. Regardless of the radiologist experience, the combination of clinical models and mpMRI provided significantly robust tools in terms of discriminatory power, and increased the AUCs compared with clinical models alone.…”

Section: Discussionsupporting

confidence: 62%

See 1 more Smart Citation

Head‐to‐head comparison between multiparametric MRI, the partin tables, memorial sloan kettering cancer center nomogram, and CAPRA score in predicting extraprostatic cancer in patients undergoing radical prostatectomy

Zanelli

Giannarini

Cereser

et al. 2019

Magnetic Resonance Imaging

View full text Add to dashboard Cite

Background It is unclear whether clinical models including the Partin tables (PT), the Memorial Sloan Kettering Cancer Center nomogram (MSKCCn), and the cancer of the prostate risk assessment (CAPRA) can benefit from incorporating multiparametric magnetic resonance imaging (mpMRI) when staging prostate cancer (PCa). Purpose To compare the accuracy of clinical models, mpMRI, and mpMRI plus clinical models in predicting stage ≥pT3 of PCa. Study Type Prospective monocentric cohort study. Population Seventy‐three patients who underwent radical prostatectomy between 2016–2018. Field Strength/Sequence 3.0T using turbo spin echo (TSE) imaging, single‐shot echoplanar diffusion‐weighted imaging, and T1‐weighted high‐resolution‐isotropic‐volume‐examination (THRIVE) contrast‐enhanced imaging. Assessment We calculated the probability of extraprostatic extension (EPE) using the PT and MSKCC, as well as the CAPRA score. Three readers with 2–8 years of experience in mpMRI independently staged PCa on imaging. Statistical Tests Receiver operating characteristics analysis and logistic regression analysis to investigate the per‐patient accuracy of mpMRI vs. clinical models vs. mpMRI plus clinical models in predicting stage ≥pT3. The alpha level was 0.05. Results Median probability for EPE and MSKCCn was 27.3% and 47.0%, respectively. Median CAPRA score was 3. Stage ≥pT3 occurred in 32.9% of patients. Areas under the curve (AUCs) were 0.62 for PT, 0.62 for MSKCCn, 0.64 for CAPRA, and 0.73–0.75 for mpMRI (readers 1–3) (P > 0.05 for all comparisons). Compared with mpMRI, the combination of mpMRI with PT or MSKCCn provided lower AUCs (P > 0.05 for all the readers), while the combination with CAPRA provided significantly higher (P < 0.05) AUCs in the case of readers 1 and 3. On multivariable analysis, mpMRI by reader 1 was the only independent predictor of stage ≥pT3 (odds ratio 7.40). Data Conclusion mpMRI was more accurate than clinical models and mpMRI plus clinical models in predicting stage ≥pT3, except for the combination of mpMRI and CAPRA in two out of three readers. Level of Evidence: 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:1604–1613.

show abstract

Section: Discussionsupporting

confidence: 81%

Section: Discussionsupporting

confidence: 62%

Head‐to‐head comparison between multiparametric MRI, the partin tables, memorial sloan kettering cancer center nomogram, and CAPRA score in predicting extraprostatic cancer in patients undergoing radical prostatectomy

Zanelli

Giannarini

Cereser

et al. 2019

Magnetic Resonance Imaging

View full text Add to dashboard Cite

show abstract

“…The limitations of the present study include that it was performed in a single European centre. Previous reports demonstrated that the characteristics of patients treated at certain European institutions may not match those treated at other European or North American institutions . Second, based on the fact that patients in the present study exclusively underwent initial biopsies, very important differences in rates of upgrading might exist at repeat biopsy, which is integral to AS protocols and is often performed in time intervals of a year.…”

Section: Discussionmentioning

confidence: 82%

Primary Gleason pattern upgrading in contemporary patients with D'Amico low‐risk prostate cancer: implications for future biomarkers and imaging modalities

et al. 2016

View full text Add to dashboard Cite

The low accuracy (invariably <70%) for HGPGU prediction in both patients with D'Amico low-risk prostate cancer and PRIAS eligibility indicates that these variables have poor predictive ability in contemporary patients. Despite HGPGU being a rare phenomenon, it may have life threatening implications and consequently alternatives such as biomarkers, genetic markers, or imaging modalities at re-biopsy are needed.

show abstract

“…This notion suggests that extensive validation may be needed before one predictive tool is hastily adopted over others. Others have argued that the nomograms may not be generalizable to all patients (56, 57). A group of investigators used the information from 44 published prostate cancer prediction tools to devise a “cancer metagram” which incorporated 16 treatment options and 10 outcomes (cancer control, morbidity and survival).…”

Section: Current Predictive Toolsmentioning

confidence: 99%

Prognostic Utility of PET in Prostate Cancer

Jadvar

2015

PET Clinics

View full text Add to dashboard Cite

Accurate prediction and assessment of relevant outcomes is important in clinical trial design and in clinical practice for selecting and sequencing appropriate individualized management of patients with prostate cancer. There have been many standard non-imaging based prediction tools for the various phases of prostate cancer. However these tools may be limited in individual cases and need updating based on the improved understanding of the underlying complex biology of the disease and the emergence of the novel targeted molecular imaging methods. A new platform of automated predictive tools that combine the independent molecular, imaging, and clinical information can contribute significantly to patient care and improve outcome. Such platform will also be of interest to regulatory agencies and payers as more emphasis is placed on supporting those interventions that have quantifiable and significant beneficial impact on patient outcome.

show abstract

Do prostate cancer nomograms give accurate information when applied to European patients?

Cited by 19 publications

References 28 publications

Head‐to‐head comparison between multiparametric MRI, the partin tables, memorial sloan kettering cancer center nomogram, and CAPRA score in predicting extraprostatic cancer in patients undergoing radical prostatectomy

Head‐to‐head comparison between multiparametric MRI, the partin tables, memorial sloan kettering cancer center nomogram, and CAPRA score in predicting extraprostatic cancer in patients undergoing radical prostatectomy

Primary Gleason pattern upgrading in contemporary patients with D'Amico low‐risk prostate cancer: implications for future biomarkers and imaging modalities

Prognostic Utility of PET in Prostate Cancer

Contact Info

Product

Resources

About