Risk prediction in diffuse large B-cell lymphoma improves when combining baseline PET features with interim PET response

Abstract

Accurate detection of patients at high risk of treatment failure following first line immunochemotherapy in diffuse large B-cell lymphoma (DLBCL) is of paramount importance as patients might benefit from early treatment escalation. Recently, we introduced the International Metabolic Prognostic Index (IMPI) based on metabolic tumor volume (MTV), age and stage that outperformed the International Prognostic Index. However, radiomic features such as the maximum distance between the largest lesion and another lesion (Dmaxbulk) or the peak standardized uptake value (SUVpeak) along with early treatment response at interim positron emission tomography (iPET) based on ΔSUVmax may have additional predictive value. We tested different models for risk prediction aiming to develop a dynamic risk tool. All patients within the PETRA database with newly diagnosed DLBCL treated with R-CHOP, who had available clinical data, baseline PET and iPET scans were included.

The optimal transformation of Dmaxbulk, SUVpeak and ΔSUVmax was determined by choosing the best fitting Cox regression model with lowest Akaike Information Criterion (AIC), while the cross-validated c-index was obtained as a measure for discrimination. Risk models were developed using clinical, baseline PET and iPET data. The best risk model was compared to the IMPI and our subsequent ClinicalPET model.

1014 patients were included in the analyses. Best baseline model included age, MTV and Dmaxbulk (AIC 3208.89, c-index 0.70). Adding iPET response further improved outcome prediction (AIC 3140.36, c-index 0.74) with wider segregation of Kaplan Meier-curves and improved rates of correct risk classification, supporting the value of a dynamic risk assessment in DLBCL.