Literature DB >> 32745161

Performance of Gene Expression Profile Tests for Prognosis in Patients With Localized Cutaneous Melanoma: A Systematic Review and Meta-analysis.

Michael A Marchetti1,2, Daniel G Coit3, Stephen W Dusza1, Ashley Yu1, LaToya McLean3, Yinin Hu3, Japbani K Nanda1, Konstantina Matsoukas4, Silvia E Mancebo2,5, Edmund K Bartlett3.   

Abstract

Importance: The performance of prognostic gene expression profile (GEP) tests for cutaneous melanoma is poorly characterized. Objective: To systematically assess the performance of commercially available GEP tests in patients with American Joint Committee on Cancer (AJCC) stage I or stage II disease. Data Sources: For this systematic review and meta-analysis, comprehensive searches of PubMed/MEDLINE, Embase, and Web of Science were conducted on December 12, 2019, for English-language studies of humans without date restrictions. Study Selection: Two reviewers identified GEP external validation studies of patients with localized melanoma. After exclusion criteria were applied, 7 studies (8%; 5 assessing DecisionDx-Melanoma and 2 assessing MelaGenix) were included. Data Extraction and Synthesis: Data were extracted using an adaptation of the Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modeling Studies (CHARMS-PF). When feasible, meta-analysis using random-effects models was performed. Risk of bias and level of evidence were assessed with the Quality in Prognosis Studies tool and an adaptation of Grading of Recommendations Assessment, Development, and Evaluation. Main Outcomes and Measures: Proportion of patients with or without melanoma recurrence correctly classified by the GEP test as being at high or low risk.
Results: In the 7 included studies, a total of 1450 study participants contributed data (age and sex unknown). The performance of both GEP tests varied by AJCC stage. Of patients tested with DecisionDx-Melanoma, 623 had stage I disease (6 true-positive [TP], 15 false-negative, 61 false-positive, and 541 true-negative [TN] results) and 212 had stage II disease (59 TP, 13 FN, 78 FP, and 62 TN results). Among patients with recurrence, DecisionDx-Melanoma correctly classified 29% with stage I disease and 82% with stage II disease. Among patients without recurrence, the test correctly classified 90% with stage I disease and 44% with stage II disease. Of patients tested with MelaGenix, 88 had stage I disease (7 TP, 15 FN, 15 FP, and 51 TN results) and 245 had stage II disease (59 TP, 19 FN, 95 FP, and 72 TN results). Among patients with recurrence, MelaGenix correctly classified 32% with stage I disease and 76% with stage II disease. Among patients without recurrence, the test correctly classified 77% with stage I disease and 43% with stage II disease. Conclusions and Relevance: The prognostic ability of GEP tests among patients with localized melanoma varied by AJCC stage and appeared to be poor at correctly identifying recurrence in patients with stage I disease, suggesting limited potential for clinical utility in these patients.

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Year:  2020        PMID: 32745161      PMCID: PMC7391179          DOI: 10.1001/jamadermatol.2020.1731

Source DB:  PubMed          Journal:  JAMA Dermatol        ISSN: 2168-6068            Impact factor:   10.282


  26 in total

1.  Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement.

Authors:  David Moher; Alessandro Liberati; Jennifer Tetzlaff; Douglas G Altman
Journal:  Ann Intern Med       Date:  2009-07-20       Impact factor: 25.391

2.  Identifying phases of investigation helps planning, appraising, and applying the results of explanatory prognosis studies.

Authors:  J A Hayden; P Côté; I A Steenstra; C Bombardier
Journal:  J Clin Epidemiol       Date:  2008-03-10       Impact factor: 6.437

3.  A guide to systematic review and meta-analysis of prognostic factor studies.

Authors:  Richard D Riley; Karel G M Moons; Kym I E Snell; Joie Ensor; Lotty Hooft; Douglas G Altman; Jill Hayden; Gary S Collins; Thomas P A Debray
Journal:  BMJ       Date:  2019-01-30

4.  Use of a prognostic gene expression profile test for T1 cutaneous melanoma: Will it help or harm patients?

Authors:  Michael A Marchetti; Edmund K Bartlett; Stephen W Dusza; Christopher K Bichakjian
Journal:  J Am Acad Dermatol       Date:  2018-12-23       Impact factor: 11.527

5.  Development of a prognostic genetic signature to predict the metastatic risk associated with cutaneous melanoma.

Authors:  Pedram Gerami; Robert W Cook; Jeff Wilkinson; Maria C Russell; Navneet Dhillon; Rodabe N Amaria; Rene Gonzalez; Stephen Lyle; Clare E Johnson; Kristen M Oelschlager; Gilchrist L Jackson; Anthony J Greisinger; Derek Maetzold; Keith A Delman; David H Lawson; John F Stone
Journal:  Clin Cancer Res       Date:  2015-01-01       Impact factor: 12.531

6.  Assessing bias in studies of prognostic factors.

Authors:  Jill A Hayden; Danielle A van der Windt; Jennifer L Cartwright; Pierre Côté; Claire Bombardier
Journal:  Ann Intern Med       Date:  2013-02-19       Impact factor: 25.391

7.  Performance of a prognostic 31-gene expression profile in an independent cohort of 523 cutaneous melanoma patients.

Authors:  Jonathan S Zager; Brian R Gastman; Sancy Leachman; Rene C Gonzalez; Martin D Fleming; Laura K Ferris; Jonhan Ho; Alexander R Miller; Robert W Cook; Kyle R Covington; Kristen Meldi-Plasseraud; Brooke Middlebrook; Lewis H Kaminester; Anthony Greisinger; Sarah I Estrada; David M Pariser; Lee D Cranmer; Jane L Messina; John T Vetto; Jeffrey D Wayne; Keith A Delman; David H Lawson; Pedram Gerami
Journal:  BMC Cancer       Date:  2018-02-05       Impact factor: 4.430

8.  Prospective validation of the prognostic 31-gene expression profiling test in primary cutaneous melanoma.

Authors:  Jennifer Keller; Theresa L Schwartz; Jason M Lizalek; Ea-Sle Chang; Ashaki D Patel; Maria Y Hurley; Eddy C Hsueh
Journal:  Cancer Med       Date:  2019-04-05       Impact factor: 4.452

9.  Practical methods for incorporating summary time-to-event data into meta-analysis.

Authors:  Jayne F Tierney; Lesley A Stewart; Davina Ghersi; Sarah Burdett; Matthew R Sydes
Journal:  Trials       Date:  2007-06-07       Impact factor: 2.279

10.  Early outcome of a 31-gene expression profile test in 86 AJCC stage IB-II melanoma patients. A prospective multicentre cohort study.

Authors:  S Podlipnik; C Carrera; A Boada; N A Richarz; J L López-Estebaranz; F Pinedo-Moraleda; M Elosua-González; M M Martín-González; R Carrillo-Gijón; P Redondo; E Moreno; J Malvehy; S Puig
Journal:  J Eur Acad Dermatol Venereol       Date:  2019-02-28       Impact factor: 6.166

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  10 in total

Review 1.  Risk Stratification of Patients with Stage I Cutaneous Melanoma Using 31-Gene Expression Profiling.

Authors:  Brian J Martin; Kyle R Covington; Ann P Quick; Robert W Cook
Journal:  J Clin Aesthet Dermatol       Date:  2021-09

2.  Clinically Significant Risk Thresholds in the Management of Primary Cutaneous Melanoma: A Survey of Melanoma Experts.

Authors:  Edmund K Bartlett; Michael A Marchetti; Douglas Grossman; Susan M Swetter; Sancy A Leachman; Clara Curiel-Lewandrowski; Stephen W Dusza; Jeffrey E Gershenwald; John M Kirkwood; Amy L Tin; Andrew J Vickers
Journal:  Ann Surg Oncol       Date:  2022-05-18       Impact factor: 4.339

3.  Bioinformatics analysis based on ferroptosis-related lncRNAs: construction of a clinical prognostic model for nasopharyngeal carcinoma and correlation analysis.

Authors:  Zuwen Dai; Yi Zhong
Journal:  Transl Cancer Res       Date:  2022-06       Impact factor: 0.496

4.  Using a Clinicopathologic and Gene Expression (CP-GEP) Model to Identify Stage I-II Melanoma Patients at Risk of Disease Relapse.

Authors:  Evalyn E A P Mulder; Iva Johansson; Dirk J Grünhagen; Dennie Tempel; Barbara Rentroia-Pacheco; Jvalini T Dwarkasing; Daniëlle Verver; Antien L Mooyaart; Astrid A M van der Veldt; Marlies Wakkee; Tamar E C Nijsten; Cornelis Verhoef; Jan Mattsson; Lars Ny; Loes M Hollestein; Roger Olofsson Bagge
Journal:  Cancers (Basel)       Date:  2022-06-09       Impact factor: 6.575

5.  An Epidemiologic Analysis of Melanoma Overdiagnosis in the United States, 1975-2017.

Authors:  Nicholas R Kurtansky; Stephen W Dusza; Allan C Halpern; Rebecca I Hartman; Alan C Geller; Ashfaq A Marghoob; Veronica M Rotemberg; Michael A Marchetti
Journal:  J Invest Dermatol       Date:  2021-12-11       Impact factor: 7.590

Review 6.  Molecular Biomarkers for Melanoma Screening, Diagnosis and Prognosis: Current State and Future Prospects.

Authors:  Dekker C Deacon; Eric A Smith; Robert L Judson-Torres
Journal:  Front Med (Lausanne)       Date:  2021-04-16

Review 7.  Bioinformatic and Machine Learning Applications in Melanoma Risk Assessment and Prognosis: A Literature Review.

Authors:  Emily Z Ma; Karl M Hoegler; Albert E Zhou
Journal:  Genes (Basel)       Date:  2021-10-30       Impact factor: 4.096

8.  Improved cutaneous melanoma survival stratification through integration of 31-gene expression profile testing with the American Joint Committee on Cancer 8th Edition Staging.

Authors:  Oliver J Wisco; Justin W Marson; Graham H Litchman; Nicholas Brownstone; Kyle R Covington; Brian J Martin; Ann P Quick; Jennifer J Siegel; Hillary G Caruso; Robert W Cook; Richard R Winkelmann; Darrell S Rigel
Journal:  Melanoma Res       Date:  2022-04-01       Impact factor: 3.199

Review 9.  Expert Consensus on the Use of Prognostic Gene Expression Profiling Tests for the Management of Cutaneous Melanoma: Consensus from the Skin Cancer Prevention Working Group.

Authors:  Aaron S Farberg; Justin W Marson; Alex Glazer; Graham H Litchman; Ryan Svoboda; Richard R Winkelmann; Nicholas Brownstone; Darrell S Rigel
Journal:  Dermatol Ther (Heidelb)       Date:  2022-03-30

Review 10.  Multidisciplinary Care of BRAF-Mutant Stage III Melanoma: A Physicians Perspective Review.

Authors:  Lynn A Cornelius; Ryan C Fields; Ahmad Tarhini
Journal:  Oncologist       Date:  2021-06-26
  10 in total

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