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... Show moreOBJECTIVE 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 num-bers 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 impair-ment. 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 Swit- zerland 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, al- though 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. Show less
Germ-line mutations in breast cancer 1, early onset (BRCA1) result in predisposition to breast and ovarian cancer. BRCA1-mutated tumors show genomic instability, mainly as a consequence of impaired... Show moreGerm-line mutations in breast cancer 1, early onset (BRCA1) result in predisposition to breast and ovarian cancer. BRCA1-mutated tumors show genomic instability, mainly as a consequence of impaired recombinatorial DNA repair. Here we identify p53-binding protein 1 (53BP1) as an essential factor for sustaining the growth arrest induced by Brca1 deletion. Depletion of 53BP1 abrogates the ATM-dependent checkpoint response and G2 cell-cycle arrest triggered by the accumulation of DNA breaks in Brca1-deleted cells. This effect of 53BP1 is specific to BRCA1 function, as 53BP1 depletion did not alleviate proliferation arrest or checkpoint responses in Brca2-deleted cells. Notably, loss of 53BP1 partially restores the homologous-recombination defect of Brca1-deleted cells and reverts their hypersensitivity to DNA-damaging agents. We find reduced 53BP1 expression in subsets of sporadic triple-negative and BRCA-associated breast cancers, indicating the potential clinical implications of our findings. Show less
