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An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
External validation of prognostic models predicting outcome after chronic subdural hematoma
Dana C Holl1,2,3, Ana Mikolic4, Jurre Blaauw5
1Department of Neurosurgery, Erasmus Medical Centre, Erasmus MC Stroke Centre, Dr Molewaterplein 40, 3015 GD, Rotterdam, The Netherlands. d.holl@erasmusmc.nl.
Insights
Existing prediction models for chronic subdural hematoma (CSH) outcomes show poor performance. Further research is needed to develop reliable prognostic tools for CSH patients.
Area of Science:
- Neurosurgery
- Clinical Epidemiology
- Medical Statistics
Background:
- Several prognostic models for chronic subdural hematoma (CSH) treatment outcomes exist.
- These models lack sufficient external validation for routine clinical use.
- Accurate outcome prediction in CSH patients remains a clinical challenge.
Purpose of the Study:
- To assess the performance of existing prognostic models for predicting outcomes in patients with CSH.
- To evaluate the calibration and discrimination of validated models using a large retrospective database.
Main Methods:
- Systematic literature search up to February 2021 for CSH prognostic models.
- External validation of identified models using a retrospective database of 2384 patients.
- Assessment of model calibration and discrimination (concordance index C).
Main Results:
- Three models were externally validated: one for 30-day mortality and two for hematoma recurrence.
- Models overestimated outcomes (e.g., 11% overestimation for mortality).
- Discriminative ability was poor to modest (C-indices ranging from 0.46 to 0.70).
Conclusions:
- Existing prognostic models demonstrate inadequate predictive performance for CSH outcomes.
- The heterogeneity of CSH patients contributes to prediction difficulties.
- Development of high-quality prognostic models with unified predictors and outcomes is warranted.
Background:
Several prognostic models for outcomes after chronic subdural hematoma (CSDH) treatment have been published in recent years. However, these models are not sufficiently validated for use in daily clinical practice. We aimed to assess the performance of existing prediction models for outcomes in patients diagnosed with CSDH.
Methods:
We systematically searched relevant literature databases up to February 2021 to identify prognostic models for outcome prediction in patients diagnosed with CSDH. For the external validation of prognostic models, we used a retrospective database, containing data of 2384 patients from three Dutch regions. Prognostic models were included if they predicted either mortality, hematoma recurrence, functional outcome, or quality of life. Models were excluded when predictors were absent in our database or available for < 150 patients in our database. We assessed calibration, and discrimination (quantified by the concordance index C) of the included prognostic models in our retrospective database.
Results:
We identified 1680 original publications of which 1656 were excluded based on title or abstract, mostly because they did not concern CSDH or did not define a prognostic model. Out of 18 identified models, three could be externally validated in our retrospective database: a model for 30-day mortality in 1656 patients, a model for 2 months, and another for 3-month hematoma recurrence both in 1733 patients. The models overestimated the proportion of patients with these outcomes by 11% (15% predicted vs. 4% observed), 1% (10% vs. 9%), and 2% (11% vs. 9%), respectively. Their discriminative ability was poor to modest (C of 0.70 [0.63-0.77]; 0.46 [0.35-0.56]; 0.59 [0.51-0.66], respectively).
Conclusions:
None of the examined models showed good predictive performance for outcomes after CSDH treatment in our dataset. This study confirms the difficulty in predicting outcomes after CSDH and emphasizes the heterogeneity of CSDH patients. The importance of developing high-quality models by using unified predictors and relevant outcome measures and appropriate modeling strategies is warranted.
