Ability of a Genomic Classifier to Predict Metastasis and Prostate Cancer-specific Mortality after Radiation or Surgery based on Needle Biopsy Specimens

Nguyen, Paul L.; Haddad, Zaid; Ross, Ashley E.; Martin, Neil E.; Deheshi, Samineh; Lam, Lucia L.C.; Chelliserry, Jijumon; Tosoian, Jeffrey J.; Lotan, Tamara L.; Spratt, Daniel E.; Stoyanova, Radka; Punnen, Sanoj; Ong, Kaye; Buerki, Christine; Aranes, Maria; Kolisnik, Tyler; Margrave, Jennifer; Yousefi, Kasra; Choeurng, Voleak; Davicioni, Elai; Trock, Bruce J.; Kane, Christopher J.; Pollack, Alan; Davis, John W.; Feng, Felix Y.; Klein, Eric A.

doi:10.1016/j.eururo.2017.05.009

Cited by 84 publications

(52 citation statements)

References 31 publications

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“…[29][30][31] The data from the current study also demonstrated a larger difference in OS compared with PCSM among these populations. Therefore, the current study data affirm NCCN guidelines indicating that caution should be applied when considering AS for men with favorable intermediate-risk disease as we await longer follow-up data regarding population-wide outcomes with AS.…”

Section: Discussionsupporting

confidence: 63%

“…In the interim, multiparametric magnetic resonance imaging or biomarker testing may help to optimally select and follow patients being treated with AS to ensure that opportunity for cure is not lost in men with more aggressive disease than initial risk stratification may suggest. [29][30][31] The data from the current study also demonstrated a larger difference in OS compared with PCSM among these populations. Although these differences in OS likely are due in part to PCSM, other factors such as patient comorbidity also may have contributed.…”

Section: Discussionsupporting

confidence: 63%

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Use and early mortality outcomes of active surveillance in patients with intermediate‐risk prostate cancer

Butler

Mahal

Lamba

et al. 2019

Cancer

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BACKGROUND: Certain patients with intermediate-risk prostate cancer (PCa) may be appropriate candidates for active surveillance (AS). In the current study, the authors sought to characterize AS use and early mortality outcomes for patients with intermediate-risk PCa in the United States. METHODS: The novel Surveillance, Epidemiology, and End Results Active Surveillance/Watchful Waiting database identified 52,940 men diagnosed with National Comprehensive Cancer Network intermediate-risk PCa (cT2b-c, Gleason score of 7, or a prostate-specific antigen level of 10-20 ng/mL) and actively managed (AS, radiotherapy, or radical prostatectomy) from 2010 through 2015. The Cuzick test assessed AS time trends, and logistic multivariable regression characterized features associated with AS. Fine-Gray and Cox modeling determined PCa-specific mortality (PCSM) and overall survival, respectively. RESULTS: The rate of AS increased from 3.7% in 2010 to 7.3% in 2015, and from 7.2% to 11.7% among men aged ≥70 years. Among men with favorable and unfavorable intermediate-risk disease, the use of AS increased from 7.2% to 14.9% and from 2.2% to 3.8%, respectively (all P value for trend, <.001). The mean age of those patients managed with AS decreased from 69.9 years to 67.9 years (P = .0004). Factors found to be associated with AS included favorable risk disease; black race; higher socioeconomic status; older age; and diagnosis in the West, Northwest, or Midwest regions of the United States. The 5-year PCSM rate was comparable to AS versus treatment among patients with low-risk and favorable intermediate-risk disease, but was worse with AS among those with unfavorable intermediate-risk disease (PCSM, 1.3% vs 0.5%; adjusted hazard ratio, 2.48 [95% CI, 1.11-5.50; P = .026]) and intermediate-risk disease overall (PCSM, 1.1% vs 0.4%; adjusted hazard ratio, 2.34 [95% CI, 1.25-4.37; P = .008]). CONCLUSIONS: The use of AS for patients with intermediate-risk PCa is increasing across the United States, particularly for older men and those with favorable intermediate-risk disease. Early estimates of cancer-specific and overall mortality rates are low with AS, although significantly higher compared with treatment. Cancer 2019;125:3164-3171.

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Section: Discussionsupporting

confidence: 63%

Section: Discussionsupporting

confidence: 63%

Use and early mortality outcomes of active surveillance in patients with intermediate‐risk prostate cancer

Butler

Mahal

Lamba

et al. 2019

Cancer

Self Cite

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“…Machine learning methods based on predictive (classification) models using RF have recently been widely applied in many diagnostic, prognostic and therapeutic studies (40)(41)(42)(43)(44)(45)(46)(47)(48)(49)(50)(51)(52). Machine learning methods based on predictive (classification) models using RF have recently been widely applied in many diagnostic, prognostic and therapeutic studies (40)(41)(42)(43)(44)(45)(46)(47)(48)(49)(50)(51)(52).…”

Section: Discussionmentioning

confidence: 99%

“…Our study provides evidence for the clinical benefits of quantitative immunophenotyping by a rational and effective marker panel followed by the use of a predictive model (diagnostic classifier), minimizing the subjectivity of commonly used expert-based assessment. Machine learning methods based on predictive (classification) models using RF have recently been widely applied in many diagnostic, prognostic and therapeutic studies (40)(41)(42)(43)(44)(45)(46)(47)(48)(49)(50)(51)(52). Hereby we also showed its utility for the evaluation of flow cytometry data.…”

Section: Discussionmentioning

confidence: 99%

Quantitative assessment of informative immunophenotypic markers increases the diagnostic value of immunophenotyping in mature CD5‐positive B‐cell neoplasms

Starostka

Kriegová

Kudělka

et al. 2018

Cytometry Part B Clinical

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“…Mortality analysis was limited due to a low rate of PCSM. [49] These retrospective evaluations provide evidence of the utility of Decipher™ testing on prostate biopsy specimens, however there is clearly a need for further prospective evaluation.…”

Section: Currently Available Testsmentioning

confidence: 99%

Tissue-based biomarkers in prostate cancer

Clinton

Bagrodia²,

Lotan³

et al. 2017

Expert Review of Precision Medicine and Drug Development

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Introduction Prostate cancer is a heterogeneous disease. Existing risk stratification tools based on standard clinlicopathologic variables (prostate specific antigen [PSA], Gleason score, and tumor stage) provide a modest degree of predictive ability. Advances in high-throughput sequencing has led to the development of several novel tissue-based biomarkers that can improve prognostication in prostate cancer management. Areas Covered The authors review commercially-available, tissue-based biomarker assays that improve upon existing risk-stratification tools in several areas of prostate cancer management, including the appropriateness of active surveillance and aiding in decision making regarding the use of adjuvant therapy. Additionally, some of the obstacles to the widespread adoption of these biomarkers and discuss several investigational sources of new biomarkers are discussed. Expert Commentary Work is ongoing to answer pertinent clinical questions in prostate cancer management including which patients should undergo biopsy, active surveillance, receive adjuvant therapy, and what systemic therapy is best in the first-line. Incorporation into novel biomarkers may allow for the incorporation of a ‘personalized’ approach to management. Further validation will be required and questions of cost must be considered before wide scale adoption of these biomarkers. Tumor heterogeneity may impose a ceiling on the prognostic ability of biomarkers using currently available techniques.

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Ability of a Genomic Classifier to Predict Metastasis and Prostate Cancer-specific Mortality after Radiation or Surgery based on Needle Biopsy Specimens

Abstract: Biopsy Decipher predicted metastasis and prostate cancer-specific mortality risk from diagnostic biopsy specimens.

Cited by 84 publications

References 31 publications

Use and early mortality outcomes of active surveillance in patients with intermediate‐risk prostate cancer

Use and early mortality outcomes of active surveillance in patients with intermediate‐risk prostate cancer

Quantitative assessment of informative immunophenotypic markers increases the diagnostic value of immunophenotyping in mature CD5‐positive B‐cell neoplasms

Tissue-based biomarkers in prostate cancer

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