Development and external validation of a clinical prediction model for functional impairment after intracranial tumor surgery

Publication

Development and external validation of a clinical prediction model for functional impairment after intracranial tumor surgery

Journal Paper/Review - Jun 12, 2020

Staartjes Victor E, Schatlo Bawarjan, Sachkova Alexandra, Bock Hans Christoph, Hussein Abdelhalim, Rohde Veit, Broekman Marike L D, Nogarede Claudine O, Lemmens Cynthia M C, Kernbach Julius M, Neuloh Georg, Bozinov Oliver, Krayenbühl Niklaus, Sarnthein Johannes, Ferroli Paolo, Regli Luca, Stienen Martin N., Solheim Ole, Sjåvik Kristin, Broggi Morgan, Zattra Costanza Maria, Vasella Flavio, Velz Julia, Schiavolin Silvia, Serra Carlo, Bartek Jiri, Fletcher-Sandersjöö Alexander, Förander Petter, Kalasauskas Darius, Renovanz Mirjam, Ringel Florian, Brawanski Konstantin R, Kerschbaumer Johannes, Freyschlag Christian F, Jakola Asgeir S, FEBNS

Citation

Staartjes V, Schatlo B, Sachkova A, Bock H, Hussein A, Rohde V, Broekman M, Nogarede C, Lemmens C, Kernbach J, Neuloh G, Bozinov O, Krayenbühl N, Sarnthein J, Ferroli P, Regli L, Stienen M, Solheim O, Sjåvik K, Broggi M, Zattra C, Vasella F, Velz J, Schiavolin S, Serra C, Bartek J, Fletcher-Sandersjöö A, Förander P, Kalasauskas D, Renovanz M, Ringel F, Brawanski K, Kerschbaumer J, Freyschlag C, Jakola A, FEBNS. Development and external validation of a clinical prediction model for functional impairment after intracranial tumor surgery. J Neurosurg 2020:1-8.

Type

Journal Paper/Review (English)

Journal

J Neurosurg 2020

Publication Date

Jun 12, 2020

Issn Electronic

1933-0693

Pages

1-8

Brief description/objective

OBJECTIVE
Decision-making for intracranial tumor surgery requires balancing the oncological benefit against the risk for resection-related impairment. Risk estimates are commonly based on subjective experience and generalized numbers from the literature, but even experienced surgeons overestimate functional outcome after surgery. Today, there is no reliable and objective way to preoperatively predict an individual patient's risk of experiencing any functional impairment.

METHODS
The authors developed a prediction model for functional impairment at 3 to 6 months after microsurgical resection, defined as a decrease in Karnofsky Performance Status of ≥ 10 points. Two prospective registries in Switzerland and Italy were used for development. External validation was performed in 7 cohorts from Sweden, Norway, Germany, Austria, and the Netherlands. Age, sex, prior surgery, tumor histology and maximum diameter, expected major brain vessel or cranial nerve manipulation, resection in eloquent areas and the posterior fossa, and surgical approach were recorded. Discrimination and calibration metrics were evaluated.

RESULTS
In the development (2437 patients, 48.2% male; mean age ± SD: 55 ± 15 years) and external validation (2427 patients, 42.4% male; mean age ± SD: 58 ± 13 years) cohorts, functional impairment rates were 21.5% and 28.5%, respectively. In the development cohort, area under the curve (AUC) values of 0.72 (95% CI 0.69-0.74) were observed. In the pooled external validation cohort, the AUC was 0.72 (95% CI 0.69-0.74), confirming generalizability. Calibration plots indicated fair calibration in both cohorts. The tool has been incorporated into a web-based application available at https://neurosurgery.shinyapps.io/impairment/.

CONCLUSIONS
Functional impairment after intracranial tumor surgery remains extraordinarily difficult to predict, although machine learning can help quantify risk. This externally validated prediction tool can serve as the basis for case-by-case discussions and risk-to-benefit estimation of surgical treatment in the individual patient.