Cancer Res Treat.  2018 Oct;50(4):1130-1139. 10.4143/crt.2017.171.

Prognostic Factors and Decision Tree for Long-Term Survival in Metastatic Uveal Melanoma

Affiliations
  • 1Department of Ophthalmology, Bellvitge University Hospital, Barcelona, Spain. dlorenzo@bellvitgehospital.cat
  • 2Department of Oncology, Vall d'Hebron University Hospital, Barcelona, Spain.
  • 3Department of Oncology, Catalan Institute of Oncology, Barcelona, Spain.
  • 4Department of Brachytherapy, Catalan Institute of Oncology, Barcelona, Spain.
  • 5Medical Research Division, IMIM–Hospital del Mar Medical Research Institute, Barcelona, Spain.

Abstract

PURPOSE
The purpose of this study was to demonstrate the existence of a bimodal survival pattern in metastatic uveal melanoma. Secondary aims were to identify the characteristics and prognostic factors associated with long-term survival and to develop a clinical decision tree.
MATERIALS AND METHODS
The medical records of 99 metastatic uveal melanoma patients were retrospectively reviewed. Patients were classified as either short (≤ 12 months) or long-term survivors (> 12 months) based on a graphical interpretation of the survival curve after diagnosis of the first metastatic lesion. Ophthalmic and oncological characteristicswere assessed in both groups.
RESULTS
Of the 99 patients, 62 (62.6%) were classified as short-term survivors, and 37 (37.4%) as long-term survivors. The multivariate analysis identified the following predictors of long-term survival: age ≤ 65 years (p=0.012) and unaltered serum lactate dehydrogenase levels (p=0.018); additionally, the size (smaller vs. larger) of the largest liver metastasis showed a trend towards significance (p=0.063). Based on the variables significantly associated with long-term survival, we developed a decision tree to facilitate clinical decision-making.
CONCLUSION
The findings of this study demonstrate the existence of a bimodal survival pattern in patients with metastatic uveal melanoma. The presence of certain clinical characteristics at diagnosis of distant disease is associated with long-term survival. A decision tree was developed to facilitate clinical decision-making and to counsel patients about the expected course of disease.

Keyword

Uveal melanoma; Neoplasm metastasis; Long-term survivors; Decision trees

MeSH Terms

Clinical Decision-Making
Decision Trees*
Diagnosis
Humans
L-Lactate Dehydrogenase
Liver
Medical Records
Melanoma*
Multivariate Analysis
Neoplasm Metastasis
Retrospective Studies
Survivors
L-Lactate Dehydrogenase

Figure

  • Fig. 1. Definition of long (> 12 mo) and short (≤ 12 mo) survival patterns from graphs showing the overall survival distribution of 99 patients with metastatic uveal melanoma. (A) The histogram provides a quick visual summary of the survival frequencies in our cohort. A left-skewed, one-peaked distribution is shown with most subjects (> 60%) located within the first 12 months of survival. From this point, a minority of patients appeared to present a more indolent course, as evidenced by the elongated and scattered survival pattern in the remaining patients. (B) The Kaplan-Meier curve for overall survival is marked with a dashed line to indicate the approximate time point of slope change. Note the sharp decline in the survival curve during the first 12 months and its subsequent stabilization (flattening slope) beyond this point.

  • Fig. 2. Kaplan-Meier plot for overall survival comparing survival patterns. Patients were divided into long-term survivors (> 12 mo, blue line) and short-term survivors (≤ 12 mo, red line). Note the wide dispersion of data among the long-term survivors over time. Estimated median survival time for long survivors was 27 months (95% confidence interval, 14.6 to 39.2) versus 5 months for short-term survivors (95% confidence interval, 3.9 to 6.1). Comparison of survival rates between groups were performed by log-rank test (p < 0.001).

  • Fig. 3. Decision tree model depicting the prognostic factors associated with long-term (> 12 mo) survival at diagnosis of the first uveal melanoma metastasis. The regression tree representation corresponds to a binary recursive partition of the feature space among the four main variables associated with long-term survival, ordered by the relative importance of each feature given by the model, as follows: categorized gamma-glutamyl transferase (GGT), categorized lactate dehydrogenase (LDH), age at metastatic diagnosis, and the largest diameter of the largest liver metastasis. The terminal nodes divided the study sample into six prognostic groups according to the probability (in bold) of long-term survival. The fraction (%) of long-surviving patients is displayed for each terminal node. The orange color shows the most favorable combination of prognostic factors for long-term survival. The characteristics associated with the most favorable outcome at first metastatic diagnosis (82% chance of long-term survival) were as follows: unaltered serum GGT, age ≤ 65 years, and diameter of the largest liver metastasis < 20 mm. By contrast, the combination of elevated LDH and GGT levels at metastatic diagnosis yielded the worst outcomes (long-term survival probability close to 0%).


Reference

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