The following is a summary of “Development of Preoperative and Postoperative Models to Predict Recurrence in Postoperative Glioma Patients: A Longitudinal Cohort Study,” published in the February 2024 issue of Oncology by Qiao et al.
Glioma recurrence, despite maximal safe resection, poses a significant clinical challenge. This study sought to discern pivotal clinical predictors influencing recurrence and craft predictive models to refine neurological diagnostics and therapeutic approaches. Conducted longitudinally, the study encompassed a sizable cohort (n = 2825) of patients with non-recurrent glioma, pathologically diagnosed and having undergone initial surgical resection between 2010 and 2018. Logistic regression and stratified Cox proportional hazards models were meticulously constructed, drawing upon the top 15 clinical variables significantly influencing outcomes, as screened by the least absolute shrinkage and selection operator (LASSO) method. The study developed preoperative and postoperative models predicting short-term (within 6 months) postoperative recurrence in glioma patients, shedding light on risk factors associated with short- and long-term recurrence in this population.
Results unveiled preoperative and postoperative logistic models predicting short-term recurrence with accuracies of 0.78 and 0.87, respectively. A spectrum of biological and early symptomatic characteristics linked to short- and long-term recurrence emerged, with age, headache, muscle weakness, tumor location, and Karnofsky score deemed significant in the preoperative model. In contrast, age, WHO grade 4, and chemotherapy or radiotherapy treatments were paramount in the postoperative period.
Subgroup-specific postoperative predictive models targeting glioblastoma and IDH wildtype subgroups demonstrated favorable discriminatory abilities, with area under the curve (AUC) values of 0.76 and 0.80, respectively. Identifying distinct risk factor combinations accommodating diverse recurrence risks among glioma patients, coupled with the visual depiction of results via nomograms, augments the clinical applicability of personalized therapeutic strategies and care regimens. Notably, a stratified Cox model identified numerous prognostic factors for long-term recurrence, thereby facilitating the formulation of comprehensive perioperative care plans, particularly for glioblastoma patients displaying a median progression-free survival (PFS) of only 11 months.
In conclusion, the constructed preoperative and postoperative models demonstrate robust predictive capabilities for short-term postoperative glioma recurrence in a substantial patient cohort. This underscores the potential for refined treatment strategies and the imperative of vigilant clinical monitoring, especially in the early postoperative period.
Source: bmccancer.biomedcentral.com/articles/10.1186/s12885-024-11996-2