| Literature DB >> 34789006 |
Mohammad A J Abdulla1, Prem Chandra2, Susanna El Akiki3, Mahmood B Aldapt1, Sundus Sardar4, Ammar Chapra4, Abdulqadir J Nashwan5, Claudio Sorio6, Luisa Tomasello7, Christian Boni6, Mohamed A Yassin1.
Abstract
OBJECTIVE: It is debatable whether BCR-ABL1 transcript type has an impact on outcome of treatment of patients with CML, and it is not widely studied whether body weight influences response to treatment. In this study, we tried to find out if any of these factors has an impact on response to treatment and outcome.Entities:
Keywords: BCR-ABL1 transcript; chronic myeloid leukemia; obesity
Mesh:
Substances:
Year: 2021 PMID: 34789006 PMCID: PMC8619745 DOI: 10.1177/10732748211038429
Source DB: PubMed Journal: Cancer Control ISSN: 1073-2748 Impact factor: 3.302
Figure 1.Box plots depicts distribution of (A) WBC at diagnosis, (B) platelet counts at diagnosis, (C) spleen size, and (D) Sokal scores at diagnosis across transcript types e13a2 and e14a2.
Figure 2.Box plots depicts distribution of (A) WBC at diagnosis, (B) platelet counts at diagnosis, (C) spleen size, and (D) Sokal scores at diagnosis across Obese and normal weight groups.
Comparison and Association of Patient Characteristics at Diagnosis With Transcript Types and Obesity.
| Parameters | Breakpoint | — | Obesity/normal weight | — | ||
|---|---|---|---|---|---|---|
| e14a2 | e13a2 | Obesity | Normal weight | |||
| Mean±SD [median (range)] | Mean±SD [median (range)] | Mean±SD [median (range)] | Mean±SD [median (range)] | |||
| Age (years) | 43.2 ± 14.5 [41 (23, 73)] | 43.1 ± 10.9 [44 (22, 69)] | 0.962 | 46.3 ± 11.9 [46 (24, 71)] | 38.5 ± 12.5 [34.5 (22, 73)] | 0.006 |
| Age at diagnosis (years) | 39.9 ± 13.7 [39 (21, 69)] | 37.8 ± 9.7 [35.5 (21, 57)] | 0.451 | 41.1 ± 11.6 [40 (21, 68)] | 35.6 ± 11.3 [32.5 (21, 69)] | 0.041 |
| BMI | 28.5 ± 9.6 [26.4 (18.7, 74.4)] | 27.6 ± 6.0 [26 (16.2, 45.3)] | 0.618 | 32.1 ± 8.0 [30.5 (25, 74.4)] | 22.3 ± 2.2 [22.8 (16.2, 24.9)] | <0.001 |
| BMI Categories | — | — | 0.434 | — | — | ≤0.0001 |
| Underweight | 0 | 1 (2.4%) | 0 | 1 (3.1%) | ||
| Normal | 17 (44.7%) | 14 (34.1%) | 0 | 31 (96.9%) | ||
| Overweight | 7 (18.4%) | 14 (34.1%) | 21 (44.7%) | 0 | ||
| Obese class I | 7 (18.4%) | 7 (17.1%) | 14 (29.8%) | 0 | ||
| Obese class II | 6 (15.8%) | 3 (7.3%) | 9 (19.1%) | 0 | ||
| Obese class III | 1 (2.6%) | 2 (4.9%) | 3 (6.4%) | 0 | ||
| Gender | — | — | 0.318 | — | — | 0.238 |
| Male | 28 (73.7%) | 34 (82.9%) | 39 (83%) | 23 (71.9%) | ||
| Female | 10 (26.3%) | 7 (17.1%) | 8 (17%) | 9 (28.1%) | ||
| WBC at diagnosis | 154.2 ± 134.9 [112.5 (5, 500)] | 165.5 ± 128.7 [121.7 (3.5, 509)] | 0.487 | 130.1 ± 120.4 [92.6 (3.3, 500)] | 198.5 ± 135.9 [157.8 (53.2, 509)] | 0.007 |
| Blasts (%) at diagnosis | 2.6 ± 2.2 [2 (0, 8)] | 3.1 ± 5.5 [2 (0, 33)] | 0.746 | 3.0 ± 5.3 [1.5 (0, 33)] | 2.7 ± 2.0 [2 (0, 6)] | 0.219 |
| Haemoglobinat diagnosis | 11.1 ± 2.1 [11 (7.2, 16)] | 10.9 ± 2.3 [10.9 (6.4, 14.8)] | 0.772 | 11.5 ± 2.2 [12.0 (6.8, 16)] | 10.3 ± 2.1 [10.4 (6.4, 14.3)] | 0.024 |
| Platelet at diagnosis | 369.7 ± 194.5 [318 (69, 895)] | 385.7 ± 354.7 [314.5 (79, 2158)] | 0.561 | 390.7 ± 345.3 [318 (69, 2158)] | 361.2 ± 185.3 [321 (86, 895)] | 0.898 |
| Spleen size at diagnosis | 17.9 ± 5.8 [16.5 (9, 29)] | 16.3 ± 4.5 [15.8 (9, 26)] | 0.214 | 15.5 ± 4.1 [15 (9, 27)] | 19.1 ± 6.0 [20 (9, 29)] | 0.022 |
| Sokal scores at diagnosis | 0.93 ± 0.32 [0.85 (0.45, 1.62)] | 0.94 ± 0.60 [0.78 (0.53, 3.58)] | 0.894 | 0.95 ± 0.56 [0.81 (0.45, 3.58)] | 0.91 ± 0.37 [0.81 (0.53, 2.12)] | 0.745 |
| Dysplasia on CBC | — | — | 0.977 | — | — | 0.627 |
| Absent | 33 (94.3%) | 34 (94.4%) | 37 (92.5%) | 30 (96.8%) | ||
| Present | 2 (5.7%) | 2 (5.6%) | 3 (7.5%) | 1 (3.2%) | ||
Chi-square Fisher Exact test (for 2*2 tables) and for more than 2*2 tables, Yates corrected Chi-square test were applied in case of small cell frequencies (50% or more cells have expected frequencies <5) as appropriate to compute respective statistical P-value.
Figure 3.Kaplan–Meier curve showed (A) cumulative incidence of major molecular remissions (MMR), (B) cumulative incidence of complete cytogenetic remissions (CCyR), and (C) cumulative incidence of deep molecular remissions (DMR) across transcript types e13a2 and e14a2.
Figure 4.Kaplan–Meier curve showed (A) cumulative incidence of major molecular remissions (MMR), (B) cumulative incidence of complete cytogenetic remissions (CCyR), and (C) cumulative incidence of deep molecular remissions (DMR) across groups by weight.
Summary of Studies Comparing the Response to Treatment Based on Manuscript Type.
| No | Reference | No. of patients with known breakpoint/transcript | Conclusion |
|---|---|---|---|
| 1 | Tefferi A et al, 1990
| 62 | No difference |
| 2 | Shepherd P et al, 1995
| 119 | No difference |
| 3 | Prejzner W, 2002
| 61 | No significant difference |
| 4 | de Lemos JA et al, 2005
| 22 | e13a2 (b2a2) better |
| 5 | Vega-Ruiz A et al, 2007
| 480 | e14a2 (b3a2) better |
| 6 | Lucas CM et al, 2009
| 71 | e14a2 better response, no difference in overall survival, pCrKL/CrKL ratio higher in e13a2 |
| 7 | Hanfstein B et al, 2014
| 1105 | Significant difference in WBC and plts, molecular response better in e14a2, no difference in cytogenetic response and overall survival |
| 8 | Jain P et al, 2016
| 481 | e14a2 better |
| 9 | Lin HX et al, 2016
| 166 | Male worse, e13a2 (b2a2) worse, male with b2a2 much worse |
| 10 | Castagnetti F et al, 2017
| 559 | e14a2 better |
| 11 | Azad NA et al, 2018
| 42 | No difference |
| 12 | D'Adda M et al, 2019
| 173 | No difference in CCyR and MMR, e14a2 better in DMR |
| 13 | Sazawal S et al, 2019
| 400 | e14a2 better |
| 14 | Greenfield G et al, 2019
| 69 | e14a2 better |
| 15 | Our study | 79 | No significant difference in molecular response |