FLIPI was developed for overall survival and established in the prerituximab era. In contrast, FLIPI-2 was designed for progression-free survival, and, in its development cohort, more than one-half of patients had been treated with rituximabcontaining regimens. Notably, the PRIMA-PI represents a simplification of FLIPI-2, by using 2 of the 5 FLIPI-2 factors, although defining prognostic groups in a different way. From the point of view of statistical learning, predictive accuracy increases with higher model complexity, whereas the generalizability to future patients can be drastically reduced with high-dimensional data. 6 To what extent the reduction of FLIPI-2 factors is at the expense of lower predictive capacity remains to be determined. A fair comparison of PRIMA-PI and FLIPI-2 using the PRIMA cohort is not possible: PRIMA-PI is expected to be overfitted to its training cohort, whereas the evaluation of FLIPI-2 on the PRIMA cohort represents an independent validation (see figure). Unfortunately, the information on lymph node size necessary for the assessment of FLIPI-2 was missing in the validation cohort for PRIMA-PI. Thus, the head-to-head comparison of PRIMA-PI and FLIPI-2 represents an open question.The PRIMA-PI defines 3 prognostic groups with different clinical courses. Of note, the variability of outcome within the prognostic groups is still substantial. Therefore, current research focuses on integrating clinical and biological markers to improve predictive power.7 At present, many groups are generating high-dimensional data to describe the heterogeneous biology of follicular lymphoma. From the statistical learning perspective, data reduction is certainly needed to derive predictive models with acceptable generalizability to future patients. Whether a simplification of clinical data that are limited in number and have shown strong prognostic effects is a reasonable approach needs to be considered in future studies.The discrimination of outcome according to prognostic groups shown by Bachy et al indicates that current treatment, despite high efficacy, still needs improvement. Per current treatment guidelines, prognostic indices such as FLIPI, FLIPI-2, and PRIMA-PI should not be used to decide on specific therapies for a patient. Future studies on prognostic factors and, more importantly, on markers predictive of treatment response might give rise to novel individualized treatment strategies in patients with follicular lymphoma.