Systematic review of risk prediction tools for primary cutaneous melanoma outcomes and validation of sentinel lymph node positivity prediction in a UK tertiary cohort

Abstract Background It is difficult for clinicians to make predictions for cancer progression or outcomes based on AJCC staging for individual patients. Models individualising risk prediction for clinical outcomes are developed using patient level data, advanced statistical techniques, and artificia...

Full description

Saved in:
Bibliographic Details
Main Authors: R. N. Manton, A. Roshan
Format: Article
Language:English
Published: Nature Portfolio 2024-11-01
Series:BJC Reports
Online Access:https://doi.org/10.1038/s44276-024-00110-5
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1846165484102221824
author R. N. Manton
A. Roshan
author_facet R. N. Manton
A. Roshan
author_sort R. N. Manton
collection DOAJ
description Abstract Background It is difficult for clinicians to make predictions for cancer progression or outcomes based on AJCC staging for individual patients. Models individualising risk prediction for clinical outcomes are developed using patient level data, advanced statistical techniques, and artificial intelligence. Methods A systematic search identified cutaneous melanoma prognostic prediction tools published between January 1985–March 2023. Population comparisons of key clinico-pathological variables, external prediction of receiver operating characteristics and calibration analysis are applied to an unselected group of patients undergoing sentinel lymph node biopsy in a UK University hospital setting (n = 1564). Results Twenty-nine models were identified which predicted survival, disease recurrence or sentinel lymph node positivity (Internal validation n = 19 and external validation n = 14). 3 out of 7 tools for sentinel node positivity were contemporaneous with available characteristics for external validation. External validation of models by Lo et al. Friedman et al. & Bertolli et al. highlighted good discriminative performance (AUC 68.1% (64.5–71.8%), 77.1% (66.8–85.7%) & 68.6% (63.3–74.1%) respectively) but were sub-optimally calibrated for the UK patient cohort (Calibration intercept & slope Friedman: −4.01 & 32.92, Lo: −1.17 & 0.44, Bertolli: −2.75 & 4.88). Conclusions This work highlights the complexity of predictive modelling and the rigorous validation process necessary to ensure accurate predictions. Our search highlights a tendency to focus on discriminative performance over calibration, and the possibility for inconsistent predictions when tools are applied to populations with differing characteristics.
format Article
id doaj-art-7799b3facb114607bb72d7e3186b0933
institution Kabale University
issn 2731-9377
language English
publishDate 2024-11-01
publisher Nature Portfolio
record_format Article
series BJC Reports
spelling doaj-art-7799b3facb114607bb72d7e3186b09332024-11-17T12:13:23ZengNature PortfolioBJC Reports2731-93772024-11-01211910.1038/s44276-024-00110-5Systematic review of risk prediction tools for primary cutaneous melanoma outcomes and validation of sentinel lymph node positivity prediction in a UK tertiary cohortR. N. Manton0A. Roshan1Cambridge University Hospitals NHS Foundation TrustCambridge University Hospitals NHS Foundation TrustAbstract Background It is difficult for clinicians to make predictions for cancer progression or outcomes based on AJCC staging for individual patients. Models individualising risk prediction for clinical outcomes are developed using patient level data, advanced statistical techniques, and artificial intelligence. Methods A systematic search identified cutaneous melanoma prognostic prediction tools published between January 1985–March 2023. Population comparisons of key clinico-pathological variables, external prediction of receiver operating characteristics and calibration analysis are applied to an unselected group of patients undergoing sentinel lymph node biopsy in a UK University hospital setting (n = 1564). Results Twenty-nine models were identified which predicted survival, disease recurrence or sentinel lymph node positivity (Internal validation n = 19 and external validation n = 14). 3 out of 7 tools for sentinel node positivity were contemporaneous with available characteristics for external validation. External validation of models by Lo et al. Friedman et al. & Bertolli et al. highlighted good discriminative performance (AUC 68.1% (64.5–71.8%), 77.1% (66.8–85.7%) & 68.6% (63.3–74.1%) respectively) but were sub-optimally calibrated for the UK patient cohort (Calibration intercept & slope Friedman: −4.01 & 32.92, Lo: −1.17 & 0.44, Bertolli: −2.75 & 4.88). Conclusions This work highlights the complexity of predictive modelling and the rigorous validation process necessary to ensure accurate predictions. Our search highlights a tendency to focus on discriminative performance over calibration, and the possibility for inconsistent predictions when tools are applied to populations with differing characteristics.https://doi.org/10.1038/s44276-024-00110-5
spellingShingle R. N. Manton
A. Roshan
Systematic review of risk prediction tools for primary cutaneous melanoma outcomes and validation of sentinel lymph node positivity prediction in a UK tertiary cohort
BJC Reports
title Systematic review of risk prediction tools for primary cutaneous melanoma outcomes and validation of sentinel lymph node positivity prediction in a UK tertiary cohort
title_full Systematic review of risk prediction tools for primary cutaneous melanoma outcomes and validation of sentinel lymph node positivity prediction in a UK tertiary cohort
title_fullStr Systematic review of risk prediction tools for primary cutaneous melanoma outcomes and validation of sentinel lymph node positivity prediction in a UK tertiary cohort
title_full_unstemmed Systematic review of risk prediction tools for primary cutaneous melanoma outcomes and validation of sentinel lymph node positivity prediction in a UK tertiary cohort
title_short Systematic review of risk prediction tools for primary cutaneous melanoma outcomes and validation of sentinel lymph node positivity prediction in a UK tertiary cohort
title_sort systematic review of risk prediction tools for primary cutaneous melanoma outcomes and validation of sentinel lymph node positivity prediction in a uk tertiary cohort
url https://doi.org/10.1038/s44276-024-00110-5
work_keys_str_mv AT rnmanton systematicreviewofriskpredictiontoolsforprimarycutaneousmelanomaoutcomesandvalidationofsentinellymphnodepositivitypredictioninauktertiarycohort
AT aroshan systematicreviewofriskpredictiontoolsforprimarycutaneousmelanomaoutcomesandvalidationofsentinellymphnodepositivitypredictioninauktertiarycohort