P44: A Tool For Predicting The Risk Of Death From Melanoma And Competing Causes At Varying Time Intervals After Diagnosis

Thursday, March 23, 2023

3:51 PM – 3:56 PM

Location: SSO HUB: Melanoma & Sarcoma Zone

Poster Presenter(s)

Alexander H. Varey, MBChB MRCS(Eng) FRACS FRCS(Plast) PhD (he/him/his)

A/Prof
Melanoma Institute Australia; Department of Plastic Surgery, Westmead Hospital; Faculty of Medicine and Health, The University of Sydney
North Sydney, New South Wales, Australia

Disclosure(s): Novartis Pharmaceuticals Australia Pty Ltd: Speaker (Terminated, May 1, 2022)

Author(s)

Alexander H. Varey, MBChB MRCS(Eng) FRACS FRCS(Plast) PhD (he/him/his)

A/Prof
Melanoma Institute Australia; Department of Plastic Surgery, Westmead Hospital; Faculty of Medicine and Health, The University of Sydney
North Sydney, New South Wales, Australia

Disclosure(s): Novartis Pharmaceuticals Australia Pty Ltd: Speaker (Terminated, May 1, 2022)
IL

Isabel Li, MRes

Biostatistician
Melanoma Institute Australia; The University of Sydney, United States

Disclosure information not submitted.
RS

Richard Scolyer, BMedSci, MBBS, MD, FRCPA, FRCPath, FAHMS

Professor
Melanoma Institute Australia and Faculty of Medicine and Health, The University of Sydney, Tissue Pathology and Diagnostic Oncology, Royal Prince Alfred Hospital and NSW Health Pathology, Sydney,, United States

Disclosure information not submitted.
John Thompson, MD

Emeritus Professor Melanoma and Surgical Oncology
Melanoma Institute Australia, The University of Sydney
North Sydney, New South Wales, Australia

Disclosure information not submitted.
SL

Serigne Lo, MSc, PhD

A/prof
Melanoma Institute Australia; The University of Sydney, United States

Disclosure(s): No financial relationships to disclose

Disclosure(s):

Alexander H. Varey, MBChB MRCS(Eng) FRACS FRCS(Plast) PhD: Novartis Pharmaceuticals Australia Pty Ltd: Speaker (Terminated, May 1, 2022)

Serigne Lo, MSc, PhD: No financial relationships to disclose

Introduction: Accurate prognostic information is essential both for melanoma patients and for their treating clinicians when making appropriately informed management decisions. Currently, prognostic estimates are based on the AJCC staging system 8^thEdition, but this applies only at the time of initial diagnosis, is based on limited tumor characteristics, and does not consider disease-free interval, patient age or risk of dying from other causes. This study presents a tool that aims to overcome these issues.

Methods: Data
were extracted from a prospectively-maintained institutional database for patients diagnosed with a primary melanoma between

1985 and 2010 inclusive. Fine and Gray multivariable modelling was performed at subsequent yearly landmarks following diagnosis (from 0-10 years) for the two competing outcomes: melanoma-specific mortality (MSM) and non-melanoma mortality (NMM). Calibration and C-statistics were used to assess model performance.

Results: 10,459 patients were included at baseline, declining at each landmark to 2753 at the 10-year one. Final model variables included age, sex, Breslow thickness, mitotic rate, ulceration, melanoma subtype, body site, N-category, sentinel node status, local status, regional status and distant status. C-statistics for predicting 5-year MSM ranged from 69.7% [95%CI: 65.7-73.6%] to 77.5% [95%CI: 76.2-78.8%] and from 67.7% [95%CI: 64.4-71.1%] to 74.4% [95%CI: 73.1-75.7%] for 10-year MSM. Five-year 5-year NMM C-statistics ranged from 83.4% [95%CI: 82.0-84.9%] to 89.4% [95%CI: 87.0-91.7%] and 10-year NMM C-statistics from 85.2% [95%CI: 84.0-86.3%] to 93.1% [95%CI: 91.4-94.8%]. Calibration was good for both MSM and NMM models for both five-year and 10-year prediction.

Conclusions: The multivariable models at yearly timepoints up to 10 years following melanoma diagnosis give accurate prognosis for both MSM and NMM as demonstrated by the high C-statistics for both five-year and 10-year timeframes. These models will be made freely available as a user-friendly online tool at www.melanomarisk.org.au, enabling clinicians to give patients personalized prognosis and optimize their care decisions.

Learning Objectives:

Upon completion, participant will be able to calculate the risks of both melanoma specific and other causes of death for patients.
Upon completion, participant will be able to calculate the mortality risks for patients taking into account the time since diagnosis.
Upon completion, participant will be able to recalculate the mortality risks for patients taking into account disease progression.