Reliability of six prognostic models to predict time‐to‐first‐treatment in patients with chronic lymphocytic leukaemia in early phase
Authors: Stefano Molica, Diana Giannarelli, Rosanna Mirabelli, Luciano Levato, Massimo Gentile, Fortunato Morabito, Emili Montserrat
Journal: American Journal of Hematology (2017)

The clinical course of chronic lymphocytic leukemia (CLL) is heterogeneous. About 40 years ago Rai and Binet1, 2 developed similar staging systems based on easily available clinical and laboratory parameters, thus allowing to stratify patients with CLL into different risk groups. However, there is significant clinical heterogeneity within each clinical stage as they do not capture the biologic diversity of the disease, which ultimately shapes disease outcomes. Moreover, about 80% of patients with CLL are currently diagnosed in early phase of the disease (Binet stage A, Rai stage 0) a situation in which the current paradigm is that treatment is only indicated in presence of active, symptomatic disease.3 However, the diagnosis of CLL, even in early phase, may trigger anxiety and uncertainness to both patients and physicians not only about outcome but also regarding need of therapy. Recent insights into the genetic and molecular pathogenesis of CLL have led to the identification of markers (e.g., IGHV mutational status, cytogenetics, mutations of TP53, NOTCH1, SF3B1, BIRC3) that add complementary prognostic information to clinical stages,4 particularly IGHV mutational status and cytogenetic abnormalities identified by FISH.5 Thus, over the last decade many proposals incorporating biomarkers in CLL prognostic models have been formulated.6-11 Whether new prognostic models can identify a group of patients with CLL in early phase in whom early therapy could be justified has not been fully investigated. To answer this question we compared the performance in predicting time-to-first treatment (TTFT) of six different prognostic models in a series of 337 newly diagnosed Binet stage A patients from several Italian Institutions who were prospectively enrolled into the O-CLL1 protocol (clinicaltrial.gov identifier: 115NCT00917540).11, 12 A summary of variables included in different prognostic models shows that mutational status of IGHV and serum level of β2-microglobulin are the parameters more frequently included in these models (Supporting information Table 1a). In addition, while 4 of 6 prognostic models contain a combination of clinic and genetic variables (i.e., 2011 MDACC, CLL-IPI, GCLLSG, CLL-01),7, 8, 10, 11 the remaining 2 include exclusively clinic (i.e., 2007 MDACC)6 or genetic (i.e., Barcelona-Brno model) parameters.9 Patients included in the present analysis were previously used to validate CLL-IPI in early CLL.12 Their median age was 61 years (range, 33-70 years) and 57.2% were men. In this patient cohort, 77.8% were Rai stage 0 and 22.2% had Rai stage I-II. With respect to prevalence of genetic parameters, 28.1% patients had unmutated IGHV, 4.5% del(11q) and 2.6% del(17p) and/or TP53 mutation. After a median follow-up of 42 months (range, 1-82 months), 91 patients (26.9%) experienced disease-progression requiring therapy. The probability of remaining free from therapy was 65% at 5 years and no plateau was observed. The analysis of the prognostic value of different prognostic models was performed by using the receiver operating characteristic (ROC) curve (AUC13). All six models showed a moderate discriminating value ranging between 0.65 and 0.78 (Supporting information Fig. 1). The AUC exceeded the threshold level of 0.70 in all models which combine clinic and genetic variables (i.e., CLL-IPI, GCLLSG, MDACC '11, CLL-01).7, 8, 10, 11 All prognostic models fared better than Rai staging (i.e., 0 vs. I-II stages) whose AUC was only 0.60 (95% CI, 0.53-0.67), which corresponds to the lower limit for defining moderate the discriminant power of a model. As far as the Barcelona-Brno biomarkers-only prognostic model9 and the 2007 MDACC clinical-only prognostic model,7 the AUCs were 0.68 and 0.65, respectively. A comparative analysis of the sensitivity, specificity, and accuracy of different models reveals the highest accuracy (74%) for the Barcelona-Brno model which relies entirely on genetic variables (i.e., IGVH mutational status, 11q deletion or 17p deletion)9 and the lowest (64%) for the 2007 MDACC proposal totally based on clinical parameters (i.e., age, gender, Rai substage, lymph node size, and β2-microglobulin),7 this underscoring the weight of genetic variables to predict TTFT (Supporting information Table 1b). The analysis on how different models may predict TTFT over time showed a prediction power (i.e., AUC) relatively stable over time, mainly for models including both clinical and genetic variables (i.e., O-CLL1, CLL-IPI, 2011 MDACC score, GCLLSG score)7, 8, 10, 11 At 12 months after diagnosis these models reached and maintained the AUC threshold level of 0.70 (Fig 1). Time-dependent ROC analysis curves of different prognostic models (i.e., 2007 MDACC, GCLLSG, 2011 MDACC, CLL-IPI, CLL-01, and Brno-Barcelona score) in predicting TTFT. In conclusion, this study shows a statistically significant but moderate prognostic value of all analyzed models to predict TTF (areas under the ROC curve: 0.65-0.74) in patients with CLL in early phase of the disease. In practical terms, these analyses indicate that in 22%-35% of the cases the prediction established by the prognostic models investigated would be wrong. This reinforces the notion that in clinical practice patients with CLL should only be treated in the presence of active disease,3 and that prognostic models can complement but not replace clinical expertise. The authors have no conflict of interest to disclose. Additional Supporting Information may be found in the online version of this article. 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