Literature DB >> 27052645

Critical Assessment of Clinical Prognostic Tools in Melanoma.

Alyson L Mahar1, Carolyn Compton2,3, Susan Halabi4, Kenneth R Hess5, Jeffrey E Gershenwald6, Richard A Scolyer7,8,9, Patti A Groome10.   

Abstract

The 7th edition American Joint Committee on Cancer (AJCC) melanoma staging system classifies patients according to prognosis. Significant within-stage heterogeneity remains and the inclusion of additional clinicopathologic and other host- and tumor-based prognostic factors have been proposed. Clinical prognostic tools have been developed for use in clinical practice to refine survival estimates. Little is known about the comparative features of tools in melanoma. We performed a systematic search of the scientific published literature for clinical prognostic tools in melanoma and web-based resources. A priori criteria were used to evaluate their quality and clinical relevance, and included intended clinical use, model development approaches, validation strategies, and performance metrics. We identified 17 clinical prognostic tools for primary cutaneous melanoma. Patients with stages I-III and T1 or thin melanoma were the most frequently considered populations. Seventy-five percent of tools were developed using data collected from patients diagnosed in 2006 or earlier, and the well-established factors of tumor thickness, ulceration, and age were included in 70 % of tools. Internal validity using cross-validation or bootstrapping techniques was performed for two tools only. Fewer than half were evaluated for external validity; however, when done, the appropriate statistical methodology was applied and results indicated good generalizability. Several clinical prognostic tools have the potential to refine survival estimates for individual melanoma patients; however, there is a great opportunity to improve these tools and to foster the development of new, validated tools by the inclusion of contemporary clinicopathological covariates and by using improved statistical and methodological approaches.

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Year:  2016        PMID: 27052645     DOI: 10.1245/s10434-016-5212-5

Source DB:  PubMed          Journal:  Ann Surg Oncol        ISSN: 1068-9265            Impact factor:   5.344


  15 in total

1.  Critical appraisal of predictive tools to assess the difficulty of laparoscopic liver resection: a systematic review.

Authors:  Julie Hallet; Patrick Pessaux; Kaitlyn A Beyfuss; Shiva Jayaraman; Pablo E Serrano; Guillaume Martel; Natalie G Coburn; Tullio Piardi; Alyson L Mahar
Journal:  Surg Endosc       Date:  2018-10-22       Impact factor: 4.584

2.  Identification of stage I/IIA melanoma patients at high risk for disease relapse using a clinicopathologic and gene expression model.

Authors:  Alexander M M Eggermont; Domenico Bellomo; Suzette M Arias-Mejias; Enrica Quattrocchi; Sindhuja Sominidi-Damodaran; Alina G Bridges; Julia S Lehman; Tina J Hieken; James W Jakub; Dennis H Murphree; Mark R Pittelkow; Jason C Sluzevich; Mark A Cappel; Sanjay P Bagaria; Charles Perniciaro; Félicia J Tjien-Fooh; Barbara Rentroia-Pacheco; Renske Wever; Martin H van Vliet; Jvalini Dwarkasing; Alexander Meves
Journal:  Eur J Cancer       Date:  2020-10-05       Impact factor: 9.162

3.  The Limitations of Standard Clinicopathologic Features to Accurately Risk-Stratify Prognosis after Resection of Intrahepatic Cholangiocarcinoma.

Authors:  Fabio Bagante; Katiuscha Merath; Malcolm H Squires; Matthew Weiss; Sorin Alexandrescu; Hugo P Marques; Luca Aldrighetti; Shishir K Maithel; Carlo Pulitano; Todd W Bauer; Feng Shen; George A Poultsides; Olivier Soubrane; Guillaume Martel; B Groot Koerkamp; Alfredo Guglielmi; Endo Itaru; Timothy M Pawlik
Journal:  J Gastrointest Surg       Date:  2018-01-19       Impact factor: 3.452

4.  Melanoma-Induced Reprogramming of Schwann Cell Signaling Aids Tumor Growth.

Authors:  Galina V Shurin; Oleg Kruglov; Fei Ding; Yan Lin; Xingxing Hao; Anton A Keskinov; Zhaoyang You; Anna E Lokshin; William A LaFramboise; Louis D Falo; Michael R Shurin; Yuri L Bunimovich
Journal:  Cancer Res       Date:  2019-03-26       Impact factor: 12.701

Review 5.  Review of diagnostic, prognostic, and predictive biomarkers in melanoma.

Authors:  Jacob S Ankeny; Brian Labadie; Jason Luke; Eddy Hsueh; Jane Messina; Jonathan S Zager
Journal:  Clin Exp Metastasis       Date:  2018-05-02       Impact factor: 5.150

Review 6.  Personalizing prognosis in colorectal cancer: A systematic review of the quality and nature of clinical prognostic tools for survival outcomes.

Authors:  Alyson L Mahar; Carolyn Compton; Susan Halabi; Kenneth R Hess; Martin R Weiser; Patti A Groome
Journal:  J Surg Oncol       Date:  2017-08-02       Impact factor: 3.454

7.  Variability in Predictions from Online Tools: A Demonstration Using Internet-Based Melanoma Predictors.

Authors:  Emily C Zabor; Daniel Coit; Jeffrey E Gershenwald; Kelly M McMasters; James S Michaelson; Arnold J Stromberg; Katherine S Panageas
Journal:  Ann Surg Oncol       Date:  2018-02-22       Impact factor: 5.344

Review 8.  Detection of cancer metastasis: past, present and future.

Authors:  Catherine Alix-Panabieres; Anthony Magliocco; Luis Enrique Cortes-Hernandez; Zahra Eslami-S; Daniel Franklin; Jane L Messina
Journal:  Clin Exp Metastasis       Date:  2021-05-07       Impact factor: 5.150

9.  Smartphone applications for triaging adults with skin lesions that are suspicious for melanoma.

Authors:  Naomi Chuchu; Yemisi Takwoingi; Jacqueline Dinnes; Rubeta N Matin; Oliver Bassett; Jacqueline F Moreau; Susan E Bayliss; Clare Davenport; Kathie Godfrey; Susan O'Connell; Abhilash Jain; Fiona M Walter; Jonathan J Deeks; Hywel C Williams
Journal:  Cochrane Database Syst Rev       Date:  2018-12-04

10.  Underexpression of Specific Interferon Genes Is Associated with Poor Prognosis of Melanoma.

Authors:  Aamir Zainulabadeen; Philip Yao; Habil Zare
Journal:  PLoS One       Date:  2017-01-23       Impact factor: 3.240

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