Clinical Scales as Predictors of Mortality in Patients with Acute Leukemia During Intensive Induction Therapy
International Journal of Clinical Oncology and Cancer Research
Volume 4, Issue 2, April 2019, Pages: 5-9
Received: Mar. 29, 2019;
Accepted: May 6, 2019;
Published: Jun. 4, 2019
Views 322 Downloads 75
Camila Dias Pastana, Faculty of Medicine, University of State of Pará, Belém, Brazil
Dafne Rosa Benzecry, Faculty of Medicine, University of State of Pará, Belém, Brazil
Josy Marinho de Lima, Department of Oncology and Hematology, University of State of Pará, Belém, Brazil
Marcos Laércio Pontes Reis, Department of Oncology and Hematology, University of State of Pará, Belém, Brazil
Thiago Xavier Carneiro, Department of Oncology and Hematology, University of State of Pará, Belém, Brazil
Follow on us
Therapy guidelines for acute leukemias (ALs) have focused on an arbitrary age cut-off as a guide for intensity of therapy. However, treatment outcomes depend on more important prognostic factors, such as performance status (PS) and the presence of comorbidities. This study aims to evaluate clinical scales as predictors of mortality in patients with acute leukemia during intensive induction therapy. This prospective cohort study included all patients diagnosed with Acute Myeloid Leukemia (AML) or Acute Lymphoblastic Leukemia (ALL) who received induction treatment at Ophir Loyola Hospital (HOL) in Belém-PA, from February 2018 to February 2019. The following scales were assessed: Eastern Cooperative Oncology Group (ECOG), Haematopoetic Cell Transplantation Comorbidity Index (HCT-CI), Cumulative Illness Rating Scale (CIRS), Charlson Comorbidity Index (CCI), Adult Comorbidity Evaluation 27 (ACE-27), Katz and Lawton scales, G8 Questionnaire and Mini Nutritional Assessment (MAN). The median age of the 40 patients included was 37 years old (range, 19-65) and sex distribution was equal. Univariate analysis showed that higher age (OR = 5.74, p 0.024), ACE 27 >0 (OR = 5.7, p 0.003) and HCT-CI >0 (OR = 3.87, p 0.02) were contributing factors to 40-day mortality, but no meaningful association was noticed with the other scales. Therefore, this study reaffirms the significant impact of comorbidities on the survival of patients with AL, suggesting that comorbidity assessment may be extremely helpful for making decisions on intensive induction therapy.
Acute Leukemia, Induction Chemotherapy, Outcomes, Comorbidity
To cite this article
Camila Dias Pastana,
Dafne Rosa Benzecry,
Josy Marinho de Lima,
Marcos Laércio Pontes Reis,
Thiago Xavier Carneiro,
Clinical Scales as Predictors of Mortality in Patients with Acute Leukemia During Intensive Induction Therapy, International Journal of Clinical Oncology and Cancer Research.
Vol. 4, No. 2,
2019, pp. 5-9.
Copyright © 2019 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/
) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Rêgo MAV, Fonseca AA. Mortality Trends from Leukemia in Salvador - Brazil, 1980 to 2012. Rev Bras Cancerol. 2015; 61 (4): 325-34.
Instituto Nacional de Câncer José Alencar Gomes da Silva. Estimate 2018: incidence of cancer in Brazil / Instituto Nacional de Câncer José Alencar Gomes da Silva. Coordenação de Prevenção e Vigilância. – Rio de Janeiro: INCA, 2017.
Righes CS, Garcia DVO, Silva PC, Almeida EB, Pellegrin JC. Epidemiological, hematological and imunophenotypic evaluation of adult patients with acute leukemia diagnosed at the Regional Hospital of Mato Grosso do Sul, Brazil. RBAC. 2017; 49 (3): 249-55.
Sorror ML, Storer BE, Fathi AT, et al. Development And Validation Of A Novel Acute Myeloid Leukemia–Composite Model To Estimate Risks Of Mortality. JAMA Oncol. 2017; 1-8.
Middeke JM, Herbst R, Parmentier S, et al. Long-Term Follow-Up and Impact of Comorbidity before Allogeneic Hematopoietic Stem Cell Transplantation in Patients with Relapsed or Refractory Acute Myeloid Leukemia—Lessons Learned from the Prospective BRIDGE Trial. Biol Blood Marrow Transplant. 2017; 23: 1491–1497.
Budziszewska BK, Pluta A, Sulek K, et al. Treatment of elderly patients with acute myeloid leukemia adjusted for performance status and presence of comorbidities: a Polish Adult Leukemia Group study. Leuk & Lymphoma. 2015; 1–8.
Short, NJ, Rytting, ME, Cortes, JE. Acute myeloid leukaemia. Lancet 2018, 392, 593–606.
Wass M, Hitz F, Schaffrath J, MullerTidow C, Muller LP. Value of Different Comorbidity Indices for Predicting Outcome in Patients with Acute Myeloid Leukemia. PLoS One. 2016; 11 (10): 1-13.
Dufva IH, GranfeldtØstg˚ard LS, Medeiros BC, et al. Epidemiology and clinical significance of secondary and therapy-related acute myeloid leukemia: a national population-based cohort study. J Clin Oncol. 2015; 33 (31): 3641-3649.
Tawfik B, Pardee TS, Isom S, et al. Comorbidity, age, and mortality among adults treated intensively for acute myeloid leukemia (AML), J Geriatr Oncol. (2015), http://dx.doi.org/10.1016/j.jgo.2015.10.182
Djunic I, Virijevic M, Novkovic A, et al. Pretreatment risk factors and importance of comorbidity for overall survival, complete remission, and early death in patients with acute myeloid leukemia. Hematology. 2012; 17(2): 53-38.
Master S, Munker R, Shi Z, Mills G, Shi R. Insurance Status and Other Non-biological Factors Predict Outcomes in Acute Myelogenous Leukemia: Analysis of Data from the National Cancer Database. Anticancer research. 2016; 36: 4915-22.
Schimansky S, Lang S, Beynon R, et al. Association between comorbidity and survival in head and neck cancer: Results from Head and Neck 5000. Head & Neck. 2018; 1–10.
Ito S, Ito H, Sato N, et al. Clinical factors associated with the therapeutic outcome of chemotherapy in very elderly cancer patients. Int J Clin Oncol. 2019. https://doi.org/10.1007/s10147-018-01385-8
Kallogjeri D, Gaynor SM, Piccirillo ML, et al. Comparison of Comorbidity Collection Methods. J Am Coll Surg. 2014; 219 (2): 245–255.
Li J, Wang C, Liu X, et al. Severe malnutrition evaluated by patient-generated subjective global assessment results in poor outcome among adult patients with acute leukemia: A retrospective cohort study. Medicine. 2018; 97 (3): 1-6.
Baumgartner A, Zueger N, Bargetzi A, et al. Association of Nutritional Parameters with Clinical Outcomes in Patients with Acute Myeloid Leukemia Undergoing Haematopoietic Stem Cell Transplantation. Ann Nutr Metab. 2016; 69: 89–98.
Pereira EEB, Sarges ESNF, Santos NB. Functional capacity evaluation of the hospitalized oncogeriatric patient. Rev Pan-Amaz Saude. 2014; 5 (4): 37-44.