Evidence map›Paper›PMID 39611693›Full record

ArticleCancer medicine2024

Individualized Prediction for Risk of Recurrence in Stage I/II Melanoma Patients With Negative Sentinel Lymph Node.

Shu-Ching Chang, Kristel Lourdault, Gary L Grunkemeier, Douglas A Hanes, Shih-Ting Chiu, Stacey Stern, Richard Essner

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Article in Cancer medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Shu-Ching ChangProvidence St. Joseph Health, Portland, Oregon, USA.ORCID 0000-0002-6534-0124
Kristel LourdaultProvidence Saint John's Cancer Institute, Santa Monica, California, USA.ORCID 0000-0003-2875-5918
Gary L GrunkemeierOregon Health & Science University, Portland, Oregon, USA.
Douglas A HanesProvidence St. Joseph Health, Portland, Oregon, USA.
Shih-Ting ChiuProvidence St. Joseph Health, Portland, Oregon, USA.
Stacey SternProvidence Saint John's Cancer Institute, Santa Monica, California, USA.
Richard EssnerProvidence Saint John's Cancer Institute, Santa Monica, California, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDespite the favorable prognosis of AJCC stage I/II melanoma patients, up to 20%-30% will develop metastases. Our objective is to predict long-term risk (probability) of recurrence in early-stage melanoma patients.

methodsA Risk Score to predict long-term recurrence was developed using Cox regression based on 2668 patients. Five clinicopathological risk factors were included. The association of the Risk Score with the risk of recurrence was evaluated using parametric models (exponential, Weibull, and Gompertz models) and compared to the Cox model using the Akaike information criterion. The discrimination of the model was measured by time-dependent ROC analyses. A calibration curve was used to evaluate the agreement between predicted and observed recurrence probabilities.

resultsThe bootstrap adjusted C-index was 0.76 (95% CI, 0.74-0.79) overall and 0.87 (0.83-0.90) and 0.82 (0.78-0.85) at one and two years, respectively, and then remained above 0.70 up to 20 years. The Gompertz model for prediction of survival from the Risk Score showed the best performance and displayed good agreement with the Kaplan-Meier curves. The calibration curve of the Gompertz model showed a good agreement between predicted and observed 2-, 5-, and 10-year risk of recurrence. Population-level analysis demonstrated a significant association of Risk Score with risk of recurrence, with 10-year risks of recurrence of 4.5%, 13.0%, and 33.7% in the first, second, and third tertiles, respectively.

conclusionWe developed a Risk Score to predict long-term risk of recurrence for early-stage melanoma patients. A Gompertz survival model fit to the Risk Score allows for individualized prediction of time-dependent recurrence risk.

Indexed as

MelanomaNeoplasm Recurrence, LocalNeoplasm StagingAdultAgedAged, 80 and overFemaleHumansKaplan-Meier EstimateMaleMiddle AgedPrognosisProportional Hazards ModelsRisk AssessmentRisk FactorsROC CurveGompertz modelnegative sentinel lymph noderisk of recurrencestage I/II melanoma

Identifiers

PMID39611693
PMCPMC11605731

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.