Literature DB >> 33600211

Development and Validation of Nomograms to Predict Local, Regional, and Distant Recurrence in Patients With Thin (T1) Melanomas.

Mary-Ann El Sharouni1,2, Tasnia Ahmed1, Alexander H R Varey1,3,4, Sjoerd G Elias5, Arjen J Witkamp6, Vigfús Sigurdsson2, Karijn P M Suijkerbuijk7, Paul J van Diest8, Richard A Scolyer1,3,9, Carla H van Gils5, John F Thompson1,3,10, Willeke A M Blokx8, Serigne N Lo1,3.   

Abstract

PURPOSE: Although the prognosis of patients with thin primary cutaneous melanomas (T1, ≤ 1.0 mm) is generally excellent, some develop recurrence. We sought to develop and validate a model predicting recurrences in patients with thin melanomas.
METHODS: A Dutch population-based cohort (n = 25,930, development set) and a cohort from an Australian melanoma treatment center (n = 2,968, validation set) were analyzed (median follow-up 6.7 and 12.0 years, respectively). Multivariable Cox models were generated for local, regional, and distant recurrence-free survival (RFS). Discrimination was assessed using Harrell's C-statistic for each outcome. Each nomogram performance was evaluated using calibration plots defining low-risk and high-risk groups as the lowest and top 5% of the nomogram risk score, respectively. The nomograms' C-statistics were compared with those of a model including the current American Joint Committee on Cancer staging parameters (T-stage and sentinel node status).
RESULTS: Local, regional, and distant recurrences were found in 209 (0.8%), 503 (1.9%), and 203 (0.8%) Dutch patients, respectively, and 23 (0.8%), 61 (2.1%), and 75 (2.5%) Australian patients, respectively. C-statistics of 0.79 (95% CI, 0.75 to 0.82) for local RFS, 0.77 (95% CI, 0.75 to 0.78) for regional RFS, and 0.80 (95% CI, 0.77 to 0.83) for distant RFS were obtained for the development model. External validation showed C-statistics of 0.80 (95% CI, 0.69 to 0.90), 0.76 (95% CI, 0.70 to 0.82), and 0.74 (95% CI, 0.69 to 0.80), respectively. Calibration plots showed a good match between predicted and observed rates. Using the nomogram, the C-statistic was increased by 9%-12% for the development cohort and by 11%-15% for the validation cohort, compared with a model including only T-stage and sentinel node status.
CONCLUSION: Most patients with thin melanomas have an excellent prognosis, but some develop recurrence. The presented nomograms can accurately identify a subgroup at high risk. An online calculator is available at www.melanomarisk.org.au.

Entities:  

Year:  2021        PMID: 33600211     DOI: 10.1200/JCO.20.02446

Source DB:  PubMed          Journal:  J Clin Oncol        ISSN: 0732-183X            Impact factor:   44.544


  8 in total

1.  Predicting bacterial infection risk in patients with ANCA-associated vasculitis in southwest China: development of a new nomogram.

Authors:  Naidan Zhang; Jiaxiang Sun; Chaixia Ji; Xiao Bao; Chenliang Yuan
Journal:  Clin Rheumatol       Date:  2022-08-02       Impact factor: 3.650

2.  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

3.  Accurate Prediction of Metachronous Liver Metastasis in Stage I-III Colorectal Cancer Patients Using Deep Learning With Digital Pathological Images.

Authors:  Chanchan Xiao; Meihua Zhou; Xihua Yang; Haoyun Wang; Zhen Tang; Zheng Zhou; Zeyu Tian; Qi Liu; Xiaojie Li; Wei Jiang; Jihui Luo
Journal:  Front Oncol       Date:  2022-04-01       Impact factor: 5.738

4.  Development and Verification of a Combined Immune- and Metabolism-Related Prognostic Signature for Hepatocellular Carcinoma.

Authors:  Yuanyuan Guo; Jing Yang; Hua Gao; Xin Tian; Xiaojian Zhang; Quancheng Kan
Journal:  Front Immunol       Date:  2022-07-08       Impact factor: 8.786

5.  Development and validation of nomograms for predicting survival in patients with de novo metastatic triple-negative breast cancer.

Authors:  Mao-Shan Chen; Peng-Cheng Liu; Jin-Zhi Yi; Li Xu; Tao He; Hao Wu; Ji-Qiao Yang; Qing Lv
Journal:  Sci Rep       Date:  2022-08-29       Impact factor: 4.996

6.  Validation of four cutaneous squamous cell carcinoma staging systems using nationwide data.

Authors:  Zoe Claire Venables; Selin Tokez; Loes M Hollestein; Antien L Mooyaart; Renate Ruth van den Bos; Brian Rous; Irene M Leigh; Tamar Nijsten; Marlies Wakkee
Journal:  Br J Dermatol       Date:  2022-03-26       Impact factor: 11.113

7.  Individualized model for predicting pathological complete response to neoadjuvant chemotherapy in patients with breast cancer: A multicenter study.

Authors:  Bei Qian; Jing Yang; Jun Zhou; Longqing Hu; Shoupeng Zhang; Min Ren; Xincai Qu
Journal:  Front Endocrinol (Lausanne)       Date:  2022-08-17       Impact factor: 6.055

8.  Penalized likelihood estimation of a mixture cure Cox model with partly interval censoring-An application to thin melanoma.

Authors:  Annabel Webb; Jun Ma; Serigne N Lô
Journal:  Stat Med       Date:  2022-04-26       Impact factor: 2.497

  8 in total

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