Prognostic significance of clinical risk models and genomic alterations in Waldenström macroglobulinemia before or after BTK inhibitor era

Abstract Background Waldenström's macroglobulinemia (WM) is an indolent B-cell lymphoma with high heterogeneity. Several clinical risk models, including IPSSWM, rIPSSWM, and MSSWM, were established before the widespread use of Bruton tyrosine kinase inhibitors (BTKi). However, it is unclear which of the pre-BTKi prognostic models has the greatest predictive power in the current era, or whether these models remain applicable for patients receiving BTKi therapy. Moreover, the prognostic significance of specific genomic alterations is still under debate in different treatment contexts. Methods This study retrospectively analyzed patients with symptomatic WM, diagnosed between June 2013 and June 2023 at the Institute of Hematology and Blood Diseases Hospital, according to the criteria of the Second International Workshop on WM. MYD88 and CXCR4 mutations were detected by Sanger sequencing, droplet digital PCR, allele-specific PCR, or targeted next-generation sequencing (NGS). Mutation status for MYD88 and CXCR4 was available for 453 and 430 patients, respectively, and NGS data were available for 292 patients. Results Our study cohort included 453 symptomatic WM patients, with 203 receiving non-BTKi therapy and 250 receiving BTKi-based therapy at any line of treatment. The median age at diagnosis was 61 (range, 28–86) years, and 71.5% were male. The median follow-up for the entire cohort was 56.6 (95%CI, 52.6–63.5) months. In the non-BTKi cohort, all three models showed significant prognostic discrimination, with rIPSSWM demonstrating the highest predictive accuracy for overall survival (OS) (C-statistic: 0.702, 95% CI, 0.624–0.781), significantly greater than that of IPSSWM (0.632, 95% CI, 0.560–0.704; P = 0.044), and comparable to MSSWM model (0.687, 95% CI, 0.614–0.760; P = 0.661). In contrast, these models failed to distinguish survival outcomes in the BTKi cohort. The rIPSSWM model still yielded the highest C-statistic (0.643, 95% CI, 0.544–0.743), but the overall discrimination of all three models was notably reduced (IPPSWM: 0.547, 95% CI, 0.451-0.644; MSSWM: 0.567, 95% CI, 0.447-0.688). Notably, among patients receiving first-line BTKi-based therapy, those classified as high-risk by any model achieved survival outcomes comparable to lower-risk patients, suggesting that upfront BTKi can overcome the adverse impact of high-risk clinical features. Given the importance of MYD88 and CXCR4 mutations in WM, we assessed the prognostic impact in patients receiving first-line BTKi-based versus non-BTKi regimens. MYD88 mutation was significantly associated with favorable outcomes exclusively in patients treated with first-line BTKi-based therapy, while CXCR4 mutations were associated with significantly inferior prognosis in both BTKi-based and non-BTKi cohorts. In the first-line BTKi cohort, multivariate analysis confirmed MYD88MUT as an independent favorable predictor for both PFS (HR 0.28; P = 0.023) and OS (HR 0.13; P = 0.003), while CXCR4MUT independently predicted poorer PFS (HR 2.21; P = 0.033) and OS (HR 3.95; P = 0.016). Conversely, in the non-BTKi cohort, only the rIPSSWM model remained a significant prognostic factor for PFS and OS. Among the 292 patients with available NGS data, we identified 112 recurrent mutations. MYD88 (87.2%) and CXCR4 (29.5%) were the most frequent, followed by TP53 (9.2%), ARID1A (7.2%), TBL1XR1 (6.5%), KMT2D or IGLL5 (5.8%), CD79B ( 5.5%). Univariate analysis showed that TP53MUT was associated with significantly worse outcomes under BTKi therapy (P = 0.005 for PFS; P < 0.001 for OS). In the non-BTKi cohort, TP53-mutated patients also had shorter PFS (5-year landmark, P = 0.041) though OS was not significantly different (P = 0.406). Additionally, in the non-BTKi cohort, mutations in TBL1XR1 were associated with inferior PFS (P = 0.043), and IGLL5 mutation correlated with worse OS (P = 0.006). Conclusions Our study demonstrates that prognostic assessment in WM should be tailored to the treatment context. Traditional clinical models (IPSSWM, rIPSSWM, and MSSWM) remain informative for patients treated with immunochemotherapy or non-targeted therapies, with rIPSSWM offering the most refined risk stratification. However, these models alone are insufficient in the BTKi era. Genetic biomarkers, particularly MYD88, CXCR4, and TP53 mutations, provide superior prognostic value for BTKi-treated patients, supporting the integration of molecular profiling into risk assessment and treatment decisions.