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The utility of a prognostic index for predicting time to first treatment in early chronic lymphocytic leukemia: the GIMEMA experience

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Haematologica, Vol 95, Issue 3, 464-469 doi:10.3324/haematol.2009.011767

The utility of a prognostic index for predicting time to first treatment in

early chronic lymphocytic leukemia: the GIMEMA experience

Stefano Molica1, Francesca R. Mauro2, Vincenzo Callea3, relli4,

Francesco Lauria5, Bruno Rotoli6, Agostino Cortelezzi7, Vincenzo Liso8, Robin

Foà2

1 Department of Hematology-Oncology, Azienda Ospedaliera Pugliese-Ciaccio,

Catanzaro, Italy;

2 Department of Cellular Biotechnologies and Hematology, Division of Hematology,

Sapienza University, Rome, Italy;

3 Department of Hematology, Ospedali Riuniti, Reggio di Calabria, Italy;

4 Biostatistics, Regina Elena National Cancer Institute, Rome, Italy;

5 Department of Hematology and Transplant, University of Siena, AOUS, Siena,

Italy;

6 Hematology Unit, Federico II University, Naples, Italy;

7 Hematology-Bone Marrow Transplant Unit, Fondazione Ospedale Maggiore Maggiore

Policlinico, Mangiagalli, Regina Elena IRCCS, Milano, Italy and

8 Hematology Section, DAP, University of Bari, Italy

Correspondence: Stefano Molica, MD, Dept. Hematology/Oncology, Azienda

Ospedaliera Pugliese-Ciaccio, Viale Pio X 88100 Catanzaro, Italy. Email:

smolica@...

Background: A prognostic index based on widely available clinical and laboratory

features was recently proposed to predict survival in patients with previously

untreated chronic lymphocytic leukemia. We assessed the utility of this index

for predicting time to first treatment in early chronic lymphocytic leukemia.

Design and Methods: An observational database of the GIMEMA (Gruppo Italiano

Malattie EMatologiche dell'Adulto), which included 310 patients with newly

diagnosed Binet stage A chronic lymphocytic leukemia who were observed at

different primary hematology centers during the period 1991 - 2000, was used for

the purpose of this study.

Results: The new prognostic index enabled Binet stage A patients to be divided

into two subgroups that differed with respect to time to first treatment

(P=0.003). The original prognostic index was derived from a database that

included cases observed at a reference academic center; these patients were

younger (P<0.0001) and had more advanced disease (P<0.0001) than those in the

current investigation, which studied community-based patients whose data were

recorded at presentation. With this in mind, we used an optimal cut-off search

to determine how best to split patients with Binet stage A disease into

different prognostic groups. According to the recursive partitioning (RPART)

model, a classification tree was built that identified three subsets of patients

who scores were 0-2 (low risk), 3-4 (intermediate risk) and 5-7 (high risk). The

probability of remaining free from therapy at 5 years was 100% in the low risk

group, 81.2% in the intermediate risk group and 61.3% in the high risk group

(P<0.0001).

Conclusions: The results of this study confirm the utility of a new prognostic

index for predicting time to first treatment in a large sample series of

community-based patients with early stage chronic lymphocytic leukemia at

presentation. Our effort to develop a revised scoring method meets the need to

separate Binet stage A patients into different prognostic groups in order to

devise individualized and tailored follow-up during the treatment-free period.

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