Optimizing detection of clinically significant prostate cancer through nomograms incorporating mri, clinical features, and advanced serum biomarkers in biopsy naïve men

Siddiqui, Mohammad Rashid; Li, Eric V.; Kumar, Sai K. S. R.; Busza, Anna; Lin, Jasmine S.; Mahenthiran, Ashorne; Aguiar, Jonathan A.; Shah, Palak; Ansbro, Brandon; Rich, Jordan; Moataz, Soliman A. S.; Keeter, Mary-Kate; Mai, Quan; Mi, Xinlei; Tosoian, Jeffrey J.; Schaeffer, Edward M.; Patel, Hiten D.; Ross, Ashley E.

doi:10.1038/s41391-023-00660-8

Cited by 15 publications

(7 citation statements)

References 20 publications

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“…In comparison to a strategy of having all the men undergo biopsy, using a probability threshold of 30% resulting from our study as a basis for biopsy to detect csPCa would result in a net decrease of roughly five needless biopsies per 100 men without missing any malignancies. Such a figure is lower than percentages reported in other studies; where Miroslav et al, 25 and Siddiqui et al 34…”

Section: Nomograms Have Been Developed and Validated In Previouscontrasting

confidence: 56%

Development and internal validation of a nomogram predicting significant prostate cancer: Is it clinically applicable in low prevalent prostate cancer countries? A multicenter study

Arafa,

Farhat,

Khan

et al. 2023

The Prostate

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BackgroundAccurately identifying aggressive prostate tumors and studying them as a separate outcome are urgently needed. Nomogram is a predictive tool using an algorithm, it has been widely applied in clinical practice to predict prognosis. We aimed to develop and internally validate a nomogram predicting clinically significant prostate cancer (csPCa).MethodsData were retrieved from the records of the two main hospitals in Riyadh, during the period 2019–2022. Significant variables associated with csPCa cases were used to develop and internally validate a novel nomogram, utilizing the C index, and calibration curves. Decision curve analysis (DCA) was used to assess its clinical utility.ResultsProstate imaging reporting and data system (PI‐RADS), smaller prostate volume, and prostate‐specific antigen (PSA) > 10 ng/mL were significantly associated with the risk csPCa, respectively. The model developed by the nomogram showed an excellent accuracy for csPCa discrimination, as indicated by area under the curve (0.83), and calibration curves. DCA showed that our model was superior and surpassed all other models with a larger net benefit for various threshold probabilities. Based on our model, at a probability threshold of 30%, biopsying patients is the equivalent of a strategy that led to an absolute 5% reduction in the number of biopsies without missing any csPCa.ConclusionThe developed nomogram consisting of PI‐RAD, total PSA, and prostate volume showed a robust predictive capacity for csPCa before prostate biopsy that may be valuable for clinical judgment to prevent needless biopsy. Yet, the small percentage (5%) of yielded unnecessary biopsies that could be saved by using such a model, cast an important question on its merit and clinical applicability.

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Section: Nomograms Have Been Developed and Validated In Previouscontrasting

confidence: 56%

Development and internal validation of a nomogram predicting significant prostate cancer: Is it clinically applicable in low prevalent prostate cancer countries? A multicenter study

Arafa,

Farhat,

Khan

et al. 2023

The Prostate

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“…20 One study recently developed flexible models that consider additional data on percentage of free PSA levels or PHI, when available, in addition to MRI to make risk predictions for biopsy-naive men. 21 The Stockholm3 test also serves as a proprietary risk calculator, including biomarker and clinical information without MRI, and although the risk calculator can be augmented with MRI data as an exercise, the additional value over sequential screening may be minor. 22 Last, an alternative approach to screening would be to use a Additionally, we found the Van Leeuwen model was poorly calibrated across all 3 settings we evaluated, arguing against its use.…”

Section: Discussionmentioning

confidence: 99%

“…The implication of these findings is that while use of MRI-based PCa risk calculators is justified in conjunction with advanced biomarkers, screening could be further optimized if the advanced biomarker value was directly incorporated into the risk calculator . One study recently developed flexible models that consider additional data on percentage of free PSA levels or PHI, when available, in addition to MRI to make risk predictions for biopsy-naive men . The Stockholm3 test also serves as a proprietary risk calculator, including biomarker and clinical information without MRI, and although the risk calculator can be augmented with MRI data as an exercise, the additional value over sequential screening may be minor .…”

Section: Discussionmentioning

confidence: 99%

Comparison of Magnetic Resonance Imaging–Based Risk Calculators to Predict Prostate Cancer Risk

Patel,

Remmers,

Ellis

et al. 2024

JAMA Netw Open

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ImportanceMagnetic resonance imaging (MRI)–based risk calculators can replace or augment traditional prostate cancer (PCa) risk prediction tools. However, few data are available comparing performance of different MRI-based risk calculators in external cohorts across different countries or screening paradigms.ObjectiveTo externally validate and compare MRI-based PCa risk calculators (Prospective Loyola University Multiparametric MRI [PLUM], UCLA [University of California, Los Angeles]-Cornell, Van Leeuwen, and Rotterdam Prostate Cancer Risk Calculator–MRI [RPCRC-MRI]) in cohorts from Europe and North America.Design, Setting, and ParticipantsThis multi-institutional, external validation diagnostic study of 3 unique cohorts was performed from January 1, 2015, to December 31, 2022. Two cohorts from Europe and North America used MRI before biopsy, while a third cohort used an advanced serum biomarker, the Prostate Health Index (PHI), before MRI or biopsy. Participants included adult men without a PCa diagnosis receiving MRI before prostate biopsy.InterventionsProstate MRI followed by prostate biopsy.Main Outcomes and MeasuresThe primary outcome was diagnosis of clinically significant PCa (grade group ≥2). Receiver operating characteristics for area under the curve (AUC) estimates, calibration plots, and decision curve analysis were evaluated.ResultsA total of 2181 patients across the 3 cohorts were included, with a median age of 65 (IQR, 58-70) years and a median prostate-specific antigen level of 5.92 (IQR, 4.32-8.94) ng/mL. All models had good diagnostic discrimination in the European cohort, with AUCs of 0.90 for the PLUM (95% CI, 0.86-0.93), UCLA-Cornell (95% CI, 0.86-0.93), Van Leeuwen (95% CI, 0.87-0.93), and RPCRC-MRI (95% CI, 0.86-0.93) models. All models had good discrimination in the North American cohort, with an AUC of 0.85 (95% CI, 0.80-0.89) for PLUM and AUCs of 0.83 for the UCLA-Cornell (95% CI, 0.80-0.88), Van Leeuwen (95% CI, 0.79-0.88), and RPCRC-MRI (95% CI, 0.78-0.87) models, with somewhat better calibration for the RPCRC-MRI and PLUM models. In the PHI cohort, all models were prone to underestimate clinically significant PCa risk, with best calibration and discrimination for the UCLA-Cornell (AUC, 0.83 [95% CI, 0.81-0.85]) model, followed by the PLUM model (AUC, 0.82 [95% CI, 0.80-0.84]). The Van Leeuwen model was poorly calibrated in all 3 cohorts. On decision curve analysis, all models provided similar net benefit in the European cohort, with higher benefit for the PLUM and RPCRC-MRI models at a threshold greater than 22% in the North American cohort. The UCLA-Cornell model demonstrated highest net benefit in the PHI cohort.Conclusions and RelevanceIn this external validation study of patients receiving MRI and prostate biopsy, the results support the use of the PLUM or RPCRC-MRI models in MRI-based screening pathways regardless of European or North American setting. However, tools specific to screening pathways incorporating advanced biomarkers as reflex tests are needed due to underprediction.

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“…Our study showed that index tumors located in the central zone, although infrequent (5.0%), had significantly worse clinical and pathological features among the three locations within the prostate gland in patients with negative surgical margins. In recent years, there has been significant progress in developing nomograms for evaluating the presence of index tumors [ 21 ], as well as in studies aimed at extracting the location information of these tumors [ 22 ]. Future comprehensive studies on index tumors in prostate cancer will strengthen our results.…”

Section: Discussionmentioning

confidence: 99%

Index tumor location affected early biochemical recurrence after radical prostatectomy in patients with negative surgical margin: a retrospective study

Ogata,

Akatsuka,

Endo

et al. 2024

BMC Urol

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Background Index tumors are the most aggressive tumors of the prostate. However, their clinical significance remains unclear. This study aimed to assess the incidence of index tumor location according to the zonal origin and whether these locations affect the prognosis after radical prostatectomy in patients with negative surgical margins. Methods This single-centered, retrospective study evaluated 1,109 consecutive patients who underwent radical prostatectomies. An index tumor was defined as the largest tumor in the prostate gland. We detected these locations based on McNeal's zonal origin using whole-mount sections. Biochemical recurrence (BCR) free survival curves were generated using the Kaplan–Meier method. Univariate and multivariate analyses using the Cox proportional hazards model were performed to determine the predictive factors for early BCR (within 1-year). Results A total of 621 patients with negative surgical margins who did not receive adjuvant therapy were included in this study. The index tumor were located in the transitional zone in 191 patients (30.8%), the peripheral zone in 399 patients (64.3%), and the central zone in 31 patients (5.0%). In total, 22 of 621 patients (3.5%) experienced early BCR and 70 patients (11.2%) experienced overall BCR at a median follow-up of 61.7 months. According to the index tumor location, the early BCR-free rates were 99.5%, 95.7 %, and 83.3% in the transitional, peripheral, and central zones, respectively. On multivariate analysis, the index tumor in the central zone was an independent predictor of early BCR with negative surgical margins following radical prostatectomy, followed by prostatectomy pathological grade, index tumor in the peripheral zone, and high prostate-specific antigen level. Conclusions We assessed the significance of index tumor location in patients with negative surgical margins following radical prostatectomy. Index tumors located in the central zone, although infrequent, were the strongest predictive factors for early BCR. Our results may allow urologists and patients to reconsider the therapeutic strategies for prostate cancer.

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Optimizing detection of clinically significant prostate cancer through nomograms incorporating mri, clinical features, and advanced serum biomarkers in biopsy naïve men

Cited by 15 publications

References 20 publications

Development and internal validation of a nomogram predicting significant prostate cancer: Is it clinically applicable in low prevalent prostate cancer countries? A multicenter study

Development and internal validation of a nomogram predicting significant prostate cancer: Is it clinically applicable in low prevalent prostate cancer countries? A multicenter study

Comparison of Magnetic Resonance Imaging–Based Risk Calculators to Predict Prostate Cancer Risk

Index tumor location affected early biochemical recurrence after radical prostatectomy in patients with negative surgical margin: a retrospective study

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