Prognosis of Chronic Lymphocytic Leukemia: Analysis of One Hundred Cases

Prognostic models for newly-diagnosed chronic lymphocytic leukaemia in adults: a systematic review and meta-analysis

BACKGROUND

Chronic lymphocytic leukaemia (CLL) is the most common cancer of the lymphatic system in Western countries. Several clinical and biological factors for CLL have been identified. However, it remains unclear which of the available prognostic models combining those factors can be used in clinical practice to predict long-term outcome in people newly-diagnosed with CLL.

OBJECTIVES

To identify, describe and appraise all prognostic models developed to predict overall survival (OS), progression-free survival (PFS) or treatment-free survival (TFS) in newly-diagnosed (previously untreated) adults with CLL, and meta-analyse their predictive performances.

SEARCH METHODS

We searched MEDLINE (from January 1950 to June 2019 via Ovid), Embase (from 1974 to June 2019) and registries of ongoing trials (to 5 March 2020) for development and validation studies of prognostic models for untreated adults with CLL. In addition, we screened the reference lists and citation indices of included studies.

SELECTION CRITERIA

We included all prognostic models developed for CLL which predict OS, PFS, or TFS, provided they combined prognostic factors known before treatment initiation, and any studies that tested the performance of these models in individuals other than the ones included in model development (i.e. 'external model validation studies'). We included studies of adults with confirmed B-cell CLL who had not received treatment prior to the start of the study. We did not restrict the search based on study design.

DATA COLLECTION AND ANALYSIS

We developed a data extraction form to collect information based on the Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies (CHARMS). Independent pairs of review authors screened references, extracted data and assessed risk of bias according to the Prediction model Risk Of Bias ASsessment Tool (PROBAST). For models that were externally validated at least three times, we aimed to perform a quantitative meta-analysis of their predictive performance, notably their calibration (proportion of people predicted to experience the outcome who do so) and discrimination (ability to differentiate between people with and without the event) using a random-effects model. When a model categorised individuals into risk categories, we pooled outcome frequencies per risk group (low, intermediate, high and very high). We did not apply GRADE as guidance is not yet available for reviews of prognostic models.

MAIN RESULTS

From 52 eligible studies, we identified 12 externally validated models: six were developed for OS, one for PFS and five for TFS. In general, reporting of the studies was poor, especially predictive performance measures for calibration and discrimination; but also basic information, such as eligibility criteria and the recruitment period of participants was often missing. We rated almost all studies at high or unclear risk of bias according to PROBAST. Overall, the applicability of the models and their validation studies was low or unclear; the most common reasons were inappropriate handling of missing data and serious reporting deficiencies concerning eligibility criteria, recruitment period, observation time and prediction performance measures. We report the results for three models predicting OS, which had available data from more than three external validation studies: CLL International Prognostic Index (CLL-IPI) This score includes five prognostic factors: age, clinical stage, IgHV mutational status, B2-microglobulin and TP53 status. Calibration: for the low-, intermediate- and high-risk groups, the pooled five-year survival per risk group from validation studies corresponded to the frequencies observed in the model development study. In the very high-risk group, predicted survival from CLL-IPI was lower than observed from external validation studies. Discrimination: the pooled c-statistic of seven external validation studies (3307 participants, 917 events) was 0.72 (95% confidence interval (CI) 0.67 to 0.77). The 95% prediction interval (PI) of this model for the c-statistic, which describes the expected interval for the model's discriminative ability in a new external validation study, ranged from 0.59 to 0.83. Barcelona-Brno score Aimed at simplifying the CLL-IPI, this score includes three prognostic factors: IgHV mutational status, del(17p) and del(11q). Calibration: for the low- and intermediate-risk group, the pooled survival per risk group corresponded to the frequencies observed in the model development study, although the score seems to overestimate survival for the high-risk group. Discrimination: the pooled c-statistic of four external validation studies (1755 participants, 416 events) was 0.64 (95% CI 0.60 to 0.67); 95% PI 0.59 to 0.68. MDACC 2007 index score The authors presented two versions of this model including six prognostic factors to predict OS: age, B2-microglobulin, absolute lymphocyte count, gender, clinical stage and number of nodal groups. Only one validation study was available for the more comprehensive version of the model, a formula with a nomogram, while seven studies (5127 participants, 994 events) validated the simplified version of the model, the index score. Calibration: for the low- and intermediate-risk groups, the pooled survival per risk group corresponded to the frequencies observed in the model development study, although the score seems to overestimate survival for the high-risk group. Discrimination: the pooled c-statistic of the seven external validation studies for the index score was 0.65 (95% CI 0.60 to 0.70); 95% PI 0.51 to 0.77.

AUTHORS' CONCLUSIONS

Despite the large number of published studies of prognostic models for OS, PFS or TFS for newly-diagnosed, untreated adults with CLL, only a minority of these (N = 12) have been externally validated for their respective primary outcome. Three models have undergone sufficient external validation to enable meta-analysis of the model's ability to predict survival outcomes. Lack of reporting prevented us from summarising calibration as recommended. Of the three models, the CLL-IPI shows the best discrimination, despite overestimation. However, performance of the models may change for individuals with CLL who receive improved treatment options, as the models included in this review were tested mostly on retrospective cohorts receiving a traditional treatment regimen. In conclusion, this review shows a clear need to improve the conducting and reporting of both prognostic model development and external validation studies. For prognostic models to be used as tools in clinical practice, the development of the models (and their subsequent validation studies) should adapt to include the latest therapy options to accurately predict performance. Adaptations should be timely.

Prognostic Value of « Total Tumor Mass Score » (TTM): A Retrospective Analysis of 130 Patients with Chronic Lymphocytic Leukemia

The validity of the clinical staging of Jaksic and Vitale for chronic lymphocytic leukemia (CLL), designated total tumor mass score (TTM), was tested in 130 consecutive and previously untreated patients followed at our institution over a 15-year period. The analysis, extended to the whole population, confirmed the prognostic value of the TTM score. Patients with a high TTM (> 9.0) had an expected median survival (EMS) of 30 months; those with a low TTM (< 8.9) had an EMS of 129 months (P < 0.001). The prognostic value of TTM remained even after adjustment was made for age, sex, lymphocyte count, TTM distribution pattern, bone marrow failure, and response to therapy. Taking into account the value of the TTM score, patients of the intermediate risk group (stage II of Rai et al.) could be divided into two subgroups with a different prognosis (EMS 200 vs. 32 months; P < 0.005). When used as a continuous quantitative parameter the TTM score may help to define response to therapy. In this study TTM response to therapy was significant for prognosis (P < 0.001), and there seems to be relationship between the degree of response and survival probability.

B-chronic lymphocytic leukaemia in Latvia: epidemiological aspects

As in western Europe and the USA, chronic lymphocytic leukaemia (CLL) in Latvia is the most prevalent type of leukaemia. A total of 1509 newly diagnosed cases of B-cell chronic lymphocytic leukaemia entered the study, 440 of whom were followed up at the Latvian Haematology Centre. The main peculiarities of the study were: 1) the higher incidence of the disease in Latvia as compared with other regions of the former USSR and with western countries, 2) a lower male-to-female ratio than in most other countries and 3) a higher morbidity among the Latvian population in comparison with the Russian. A positive correlation between the disease stage and survival was confirmed, but no precise individual prognosis in an early stage of the disease was possible.

Timing of diagnosis and lymphocyte accumulation patterns in chronic lymphocytic leukemia: analysis of their clinical significance

In order to evaluate the clinical significance of the timing of diagnosis in chronic lymphocytic leukemia (CLL), we studied the diagnostic latency (DL), a variable related both to lymphocyte count and to lymphocyte doubling time (LDT), which points out the interval between the date of CLL diagnosis and the time at which it could have been made (lymphocyte count in peripheral blood of at least 5.0 x 10(9)/l). In two different series accounting for 221 previously untreated CLL patients the trends of the DL tended to decrease as the risk increased. In other words, the more advanced the clinical stage the shorter the DL. On the other hand, the values of lymphocyte accumulation rate (LAR), which defines the speed at which the number of lymphocytes increases over the time, were significantly lower in earlier stages of disease. Both DL and LAR had a significant impact on survival when investigated by means of univariate analysis. In a Cox's regression analysis applied to a training set of 122 patients, the combination of international clinical stages, LAR and age had the strongest value in predicting survival. The resulting model was validated in an independent subset of 99 patients (test-set cases) leading to a classification of patients into low-, intermediate-, and high-risk groups with 5-year survival rates of 89%, 31% and 8%, respectively, and with distinctively different annual mortality rates (p less than 0.001). Finally, when multivariate analysis was applied to study disease progression, LAR was the first variable to enter the regression model (p = 0.0001).

Prognostic value of the lymphocyte doubling time in chronic lymphocytic leukemia

The prognostic value of lymphocyte doubling time (LDT), expressed in months and obtained by means of a linear regression, has been studied in 99 previously untreated chronic lymphocytic leukemia (CLL) patients. LDT is defined as the period of time needed for lymphocytes to double in number the amount found at diagnosis. When the analysis was extended to the whole population, it showed clear differences in the life expectancy of patients with LDT of less than or equal to 12 months (median survival, 36 months; relative death rate [O/E]1.57) compared with those with LDT of more than 12 months (median survival not yet reached; O/E, 0.37) (P less than 0.001). The significance of LDT remained even after adjustments were made for age, sex, lymphocyte count, anemia, and thrombocytopenia. The lack of statistical significance after adjustment for Binet's clinical stage corresponds to the fact that clinical stages are not distributed homogeneously, high LDT being more frequently associated with earlier stages and low LDT with more advanced forms of the disease (P less than 0.001). In this study LDT was a useful parameter in predicting disease progression. Patients in Stages A and B and with rapidly increasing lymphocytes counts became worse more frequently (33.3% and 29.1%, respectively, at 12 months after diagnosis) than those with a slow increase (no change in clinical stage at 12 months). It is concluded that since LDT appears to predict the progression of the disease, it is useful in the clinical management of CLL.