A prognostic algorithm including a modified version of MD Anderson Cancer Center (MDACC) score predicts time to first treatment of patients with clinical monoclonal lymphocytosis (cMBL)/Rai stage 0 chronic lymphocytic leukemia (CLL)

Lymphocyte Doubling Time As A Key Prognostic Factor To Predict Time To First Treatment In Early-Stage Chronic Lymphocytic Leukemia

The prognostic role of lymphocyte doubling time (LDT) in chronic lymphocytic leukemia (CLL) was recognized more than three decades ago when the neoplastic clone’s biology was almost unknown. LDT was defined as the time needed for the peripheral blood lymphocyte count to double the of the initial observed value. Herein, the LDT prognostic value for time to first treatment (TTFT) was explored in our prospective O-CLL cohort and validated in in two additional CLL cohorts. Specifically, newly diagnosed Binet stage A CLL patients from 40 Italian Institutions, representative of the whole country, were prospectively enrolled into the O-CLL1-GISL protocol (clinicaltrial.gov identifier: NCT00917540). Two independent cohorts of newly diagnosed CLL patients recruited respectively at the Division of Hematology in Novara, Italy, and at the Hospital Clinic in Barcelona, Spain, were utilized as validation cohorts. In the training cohort, TTFT of patients with LDT >12 months was significantly longer related to those with a shorter LDT. At Cox multivariate regression model, LDT ≤ 12 months maintained a significant independent relationship with shorter TTFT along with IGHV unmutated (IGHVunmut) status, 11q and 17p deletions, elevated β2M, Rai stage I-II, and NOTCH1 mutations. Based on these statistics, two regression models were constructed including the same prognostic factors with or without the LDT. The model with the LTD provided a significantly better data fitting (χ² = 8.25, P=0.0041). The risk prediction developed including LDT had better prognostic accuracy than those without LDT. Moreover, the Harrell’C index for the scores including LDT were higher than those without LDT, although the accepted 0.70 threshold exceeded in both cases. These findings were also confirmed when the same analysis was carried out according to TTFT’s explained variation. When data were further analyzed based on the combination between LDT and IGHV mutational status in the training and validation cohorts, IGHVunmut and LDT>12months group showed a predominant prognostic role over IGHVmut LTD ≤ 12 months (P=0.006) in the O-CLL validation cohort. However, this predominance was of borden-line significance (P=0.06) in the Barcelona group, while the significant prognostic impact was definitely lost in the Novara group. Overall, in this study, we demonstrated that LDT could be re-utilized together with the more sophisticated prognostic factors to manage the follow-up plans for Binet stage A CLL patients.

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.

A laboratory-based scoring system predicts early treatment in Rai 0 chronic lymphocytic leukemia

We present a laboratory-based prognostic calculator (designated CRO score) to risk stratify treatment-free survival in early stage (Rai 0) chronic lymphocytic leukemia (CLL) developed using a training-validation model in a series of 1,879 cases from Italy, the United Kingdom and the United States. By means of regression analysis, we identified five prognostic variables with weighting as follows: deletion of the short arm of chromosome 17 and unmutated immunoglobulin heavy chain gene status, 2 points; deletion of the long arm of chromosome 11, trisomy of chromosome 12, and white blood cell count >32.0x10³/microliter, 1 point. Low-, intermediate- and high-risk categories were established by recursive partitioning in a training cohort of 478 cases, and then validated in four independent cohorts of 144 / 395 / 540 / 322 cases, as well as in the composite validation cohort. Concordance indices were 0.75 in the training cohort and ranged from 0.63 to 0.74 in the four validation cohorts (0.69 in the composite validation cohort). These findings advocate potential application of our novel prognostic calculator to better stratify early-stage CLL, and aid case selection in risk-adapted treatment for early disease. Furthermore, they support immunocytogenetic analysis in Rai 0 CLL being performed at the time of diagnosis to aid prognosis and treatment, particularly in today's chemofree era.

Presenting features and treatment outcomes of chronic lymphocytic leukaemia in a resource poor Southern Nigeria

Background

Chronic lymphocytic leukaemia is a relatively common haematological malignancy affecting older adults, accounting for about 20% of haematological malignancies in Nigeria. Diagnosis of this disease depends on the demonstration of clonal lymphocytosis > 5 × 109/L with a characteristic immunophenotypic pattern amidst other clinical and laboratory features.

Objectives

To determine the predominant clinical and laboratory features of CLL at presentation and their relationship with patient survival. This study also aims at examining the relationship between treatment protocol and outcome.

Methods

This is a retrospective study with 8 years data (2010–2018) collected from four different centers. Data was analyzed using SPSS 20.0.

Results

There were a total of 97 cases, with a male: female ratio of 1.1:1. The median age at presentation was 59 years. Approximately 55% of the patients presented at Binet stage C, with splenomegaly in 93.2% and 78% were anaemic. The mean white cell count was 137.9 ± 14.7 × 109/L, with a median absolute lymphocyte count of 86 × 109/L. The commonest treatment regimen was chlorambucil and prednisolone and males had a superior response. The number of chemotherapy cycles, serum alkaline phosphatase and aspartate transaminase correlated positively with duration of survival. Mortality rate over the five year period was 14.3%.

Conclusion

CLL was found to present in younger patients when compared to previous studies with a median age of 57 years at diagnosis. Our study showed a slight female preponderance and better response to therapy in males. Majority of the patients presented in Binet stage C and were treated with chlorambucil-based drug combinations compared to more current treatment with Fludarabine-based combinations. A high serum alanine transaminase and alkaline phosphatase was found to positively correlate with survival amongst this patient population

Prognostic signature and clonality pattern of recurrently mutated genes in inactive chronic lymphocytic leukemia

An increasing numbers of patients are being diagnosed with asymptomatic early-stage chronic lymphocytic leukemia (CLL), with no treatment indication at baseline. We applied a high-throughput deep-targeted analysis, especially designed for covering widely TP53 and ATM genes, in 180 patients with inactive disease at diagnosis, to test the independent prognostic value of CLL somatic recurrent mutations. We found that 40/180 patients harbored at least one acquired variant with ATM (n=17, 9.4%), NOTCH1 (n=14, 7.7%), TP53 (n=14, 7.7%) and SF3B1 (n=10, 5.5%) as most prevalent mutated genes. Harboring one ‘sub-Sanger' TP53 mutation granted an independent 3.5-fold increase of probability of needing treatment. Those patients with a double-hit ATM lesion (mutation+11q deletion) had the shorter median time to first treatment (17 months). We found that a genomic variable: TP53 mutations, most of them under the sensitivity of conventional techniques; a cell phenotypic factor: CD38-positive expression; and a classical marker as β2-microglobulin, remained as the unique independent predictors of outcome. The high-throughput determination of TP53 status, particularly in this set of patients frequently lacking high-risk chromosomal aberrations, emerges as a key step, not only for prediction modeling, but also for exploring mutation-specific therapeutic approaches and minimal residual disease monitoring.

Telomere analysis to predict chronic lymphocytic leukemia outcome: a STELA test to change clinical practice?

Defining the prognosis of individual chronic lymphocytic leukemia patients remains a significant clinical challenge. Consequently, there is a need to identify tests that can provide reliable personalized risk assessments. Here we discuss the problems associated with the currently used prognostic markers and emphasize the potential for using high-resolution telomere length analysis (STELA) for the accurate prediction of clinical outcome. Given the development of targeted, less toxic therapeutics in chronic lymphocytic leukemia, it is crucial to accurately identify those patients who might benefit from early treatment and equally those who may not require treatment at all. In this context, there is also a clear need for dependable predictive markers of response to drugs so that optimal treatment decisions can be made for individual patients.