Personalized decision-making for aneurysm treatment of aneurysmal subarachnoid hemorrhage: development and validation of a clinical prediction tool
Abstract Background In patients with aneurysmal subarachnoid hemorrhage suitable for endovascular coiling and neurosurgical clip-reconstruction, the aneurysm treatment decision-making process could be improved by considering heterogeneity of treatment effect and durability of treatment. We aimed to...
| Main Authors: | , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2024-02-01
|
| Series: | BMC Neurology |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12883-024-03546-x |
| _version_ | 1797274257879728128 |
|---|---|
| author | Jordi de Winkel Bob Roozenbeek Simone A. Dijkland Ruben Dammers Pieter-Jan van Doormaal Mathieu van der Jagt David van Klaveren Diederik W. J. Dippel Hester F. Lingsma |
| author_facet | Jordi de Winkel Bob Roozenbeek Simone A. Dijkland Ruben Dammers Pieter-Jan van Doormaal Mathieu van der Jagt David van Klaveren Diederik W. J. Dippel Hester F. Lingsma |
| author_sort | Jordi de Winkel |
| collection | DOAJ |
| description | Abstract Background In patients with aneurysmal subarachnoid hemorrhage suitable for endovascular coiling and neurosurgical clip-reconstruction, the aneurysm treatment decision-making process could be improved by considering heterogeneity of treatment effect and durability of treatment. We aimed to develop and validate a tool to predict individualized treatment benefit of endovascular coiling compared to neurosurgical clip-reconstruction. Methods We used randomized data (International Subarachnoid Aneurysm Trial, n = 2143) to develop models to predict 2-month functional outcome and to predict time-to-rebleed-or-retreatment. We modeled for heterogeneity of treatment effect by adding interaction terms of treatment with prespecified predictors and with baseline risk of the outcome. We predicted outcome with both treatments and calculated absolute treatment benefit. We described the patient characteristics of patients with ≥ 5% point difference in the predicted probability of favorable functional outcome (modified Rankin Score 0–2) and of no rebleed or retreatment within 10 years. Model performance was expressed with the c-statistic and calibration plots. We performed bootstrapping and leave-one-cluster-out cross-validation and pooled cluster-specific c-statistics with random effects meta-analysis. Results The pooled c-statistics were 0.72 (95% CI: 0.69–0.75) for the prediction of 2-month favorable functional outcome and 0.67 (95% CI: 0.63–0.71) for prediction of no rebleed or retreatment within 10 years. We found no significant interaction between predictors and treatment. The average predicted benefit in favorable functional outcome was 6% (95% CI: 3–10%) in favor of coiling, but 11% (95% CI: 9–13%) for no rebleed or retreatment in favor of clip-reconstruction. 134 patients (6%), young and in favorable clinical condition, had negligible functional outcome benefit of coiling but had a ≥ 5% point benefit of clip-reconstruction in terms of durability of treatment. Conclusions We show that young patients in favorable clinical condition and without extensive vasospasm have a negligible benefit in functional outcome of endovascular coiling – compared to neurosurgical clip-reconstruction – while at the same time having a substantially lower probability of retreatment or rebleeding from neurosurgical clip-reconstruction – compared to endovascular coiling. The SHARP prediction tool ( https://sharpmodels.shinyapps.io/sharpmodels/ ) could support and incentivize a multidisciplinary discussion about aneurysm treatment decision-making by providing individualized treatment benefit estimates. |
| first_indexed | 2024-03-07T14:55:48Z |
| format | Article |
| id | doaj.art-c1c6db445a264d6d8fa6a47fc037ec96 |
| institution | Directory Open Access Journal |
| issn | 1471-2377 |
| language | English |
| last_indexed | 2024-03-07T14:55:48Z |
| publishDate | 2024-02-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Neurology |
| spelling | doaj.art-c1c6db445a264d6d8fa6a47fc037ec962024-03-05T19:28:05ZengBMCBMC Neurology1471-23772024-02-0124111110.1186/s12883-024-03546-xPersonalized decision-making for aneurysm treatment of aneurysmal subarachnoid hemorrhage: development and validation of a clinical prediction toolJordi de Winkel0Bob Roozenbeek1Simone A. Dijkland2Ruben Dammers3Pieter-Jan van Doormaal4Mathieu van der Jagt5David van Klaveren6Diederik W. J. Dippel7Hester F. Lingsma8Department of Neurology, Erasmus MC University Medical Center RotterdamDepartment of Neurology, Erasmus MC University Medical Center RotterdamDepartment of Neurology, Erasmus MC University Medical Center Rotterdam Department of Neurosurgery, Erasmus MC University Medical Center RotterdamDepartment of Radiology and Nuclear Medicine, Erasmus MC University Medical Center RotterdamDepartment of Intensive Care Adults, Erasmus MC University Medical Center RotterdamDepartment of Public Health, Erasmus MC University Medical Center RotterdamDepartment of Neurology, Erasmus MC University Medical Center RotterdamDepartment of Public Health, Erasmus MC University Medical Center RotterdamAbstract Background In patients with aneurysmal subarachnoid hemorrhage suitable for endovascular coiling and neurosurgical clip-reconstruction, the aneurysm treatment decision-making process could be improved by considering heterogeneity of treatment effect and durability of treatment. We aimed to develop and validate a tool to predict individualized treatment benefit of endovascular coiling compared to neurosurgical clip-reconstruction. Methods We used randomized data (International Subarachnoid Aneurysm Trial, n = 2143) to develop models to predict 2-month functional outcome and to predict time-to-rebleed-or-retreatment. We modeled for heterogeneity of treatment effect by adding interaction terms of treatment with prespecified predictors and with baseline risk of the outcome. We predicted outcome with both treatments and calculated absolute treatment benefit. We described the patient characteristics of patients with ≥ 5% point difference in the predicted probability of favorable functional outcome (modified Rankin Score 0–2) and of no rebleed or retreatment within 10 years. Model performance was expressed with the c-statistic and calibration plots. We performed bootstrapping and leave-one-cluster-out cross-validation and pooled cluster-specific c-statistics with random effects meta-analysis. Results The pooled c-statistics were 0.72 (95% CI: 0.69–0.75) for the prediction of 2-month favorable functional outcome and 0.67 (95% CI: 0.63–0.71) for prediction of no rebleed or retreatment within 10 years. We found no significant interaction between predictors and treatment. The average predicted benefit in favorable functional outcome was 6% (95% CI: 3–10%) in favor of coiling, but 11% (95% CI: 9–13%) for no rebleed or retreatment in favor of clip-reconstruction. 134 patients (6%), young and in favorable clinical condition, had negligible functional outcome benefit of coiling but had a ≥ 5% point benefit of clip-reconstruction in terms of durability of treatment. Conclusions We show that young patients in favorable clinical condition and without extensive vasospasm have a negligible benefit in functional outcome of endovascular coiling – compared to neurosurgical clip-reconstruction – while at the same time having a substantially lower probability of retreatment or rebleeding from neurosurgical clip-reconstruction – compared to endovascular coiling. The SHARP prediction tool ( https://sharpmodels.shinyapps.io/sharpmodels/ ) could support and incentivize a multidisciplinary discussion about aneurysm treatment decision-making by providing individualized treatment benefit estimates.https://doi.org/10.1186/s12883-024-03546-xSubarachnoid hemorrhageIntracranial aneurysmPrognosisPersonalized decision making |
| spellingShingle | Jordi de Winkel Bob Roozenbeek Simone A. Dijkland Ruben Dammers Pieter-Jan van Doormaal Mathieu van der Jagt David van Klaveren Diederik W. J. Dippel Hester F. Lingsma Personalized decision-making for aneurysm treatment of aneurysmal subarachnoid hemorrhage: development and validation of a clinical prediction tool BMC Neurology Subarachnoid hemorrhage Intracranial aneurysm Prognosis Personalized decision making |
| title | Personalized decision-making for aneurysm treatment of aneurysmal subarachnoid hemorrhage: development and validation of a clinical prediction tool |
| title_full | Personalized decision-making for aneurysm treatment of aneurysmal subarachnoid hemorrhage: development and validation of a clinical prediction tool |
| title_fullStr | Personalized decision-making for aneurysm treatment of aneurysmal subarachnoid hemorrhage: development and validation of a clinical prediction tool |
| title_full_unstemmed | Personalized decision-making for aneurysm treatment of aneurysmal subarachnoid hemorrhage: development and validation of a clinical prediction tool |
| title_short | Personalized decision-making for aneurysm treatment of aneurysmal subarachnoid hemorrhage: development and validation of a clinical prediction tool |
| title_sort | personalized decision making for aneurysm treatment of aneurysmal subarachnoid hemorrhage development and validation of a clinical prediction tool |
| topic | Subarachnoid hemorrhage Intracranial aneurysm Prognosis Personalized decision making |
| url | https://doi.org/10.1186/s12883-024-03546-x |
| work_keys_str_mv | AT jordidewinkel personalizeddecisionmakingforaneurysmtreatmentofaneurysmalsubarachnoidhemorrhagedevelopmentandvalidationofaclinicalpredictiontool AT bobroozenbeek personalizeddecisionmakingforaneurysmtreatmentofaneurysmalsubarachnoidhemorrhagedevelopmentandvalidationofaclinicalpredictiontool AT simoneadijkland personalizeddecisionmakingforaneurysmtreatmentofaneurysmalsubarachnoidhemorrhagedevelopmentandvalidationofaclinicalpredictiontool AT rubendammers personalizeddecisionmakingforaneurysmtreatmentofaneurysmalsubarachnoidhemorrhagedevelopmentandvalidationofaclinicalpredictiontool AT pieterjanvandoormaal personalizeddecisionmakingforaneurysmtreatmentofaneurysmalsubarachnoidhemorrhagedevelopmentandvalidationofaclinicalpredictiontool AT mathieuvanderjagt personalizeddecisionmakingforaneurysmtreatmentofaneurysmalsubarachnoidhemorrhagedevelopmentandvalidationofaclinicalpredictiontool AT davidvanklaveren personalizeddecisionmakingforaneurysmtreatmentofaneurysmalsubarachnoidhemorrhagedevelopmentandvalidationofaclinicalpredictiontool AT diederikwjdippel personalizeddecisionmakingforaneurysmtreatmentofaneurysmalsubarachnoidhemorrhagedevelopmentandvalidationofaclinicalpredictiontool AT hesterflingsma personalizeddecisionmakingforaneurysmtreatmentofaneurysmalsubarachnoidhemorrhagedevelopmentandvalidationofaclinicalpredictiontool |