Juan Eduardo Megías-Vericat1, David Martínez-Cuadrón1,2, Joaquín Martínez López3, Juan Miguel Bergua4, Mar Tormo5, Josefina Serrano6, Ataulfo González7, Jaime Pérez de Oteyza8, Susana Vives9, Belén Vidriales10, Pilar Herrera11, Juan Antonio Vera12, Aurelio López Martínez13, Adolfo de la Fuente14, Mª Lourdes Amador15, José-Ángel Hernández-Rivas16, Mª Ángeles Fernández17, Carlos Javier Cerveró18, Daniel Morillo19, Pilar Hernández Campo20, Julián Gorrochategui20, Daniel Primo20, José Luis Rojas20, Margarita Guenova21, Joan Ballesteros20, Miguel Sanz1,2 and Pau Montesinos1,2 on behalf of the Spanish PETHEMA group.
1 Hospital Universitari i Politècnic La Fe, Valencia, Spain.
2 CIBERONC, Instituto Carlos III, Madrid, Spain.
3 Hospital Universitario 12 de Octubre, UCM, CNIO, CIBERONC, Madrid, Spain.
4 Hospital San Pedro de Alcántara, Cáceres, Spain.
5 Hospital Clínico Universitario, Valencia, Spain.
6 Hospital Universitario Reina Sofía, Córdoba, Spain.
7 Hospital Universitario Clínico San Carlos, Madrid, Spain.
8 Hospital de Madrid Norte Sanchinarro, Madrid, Spain.
9 ICO-Hospital Germans Trias i Pujol, Josep Carreras Leukemia Research Institute, Universitat Autònoma de Barcelona, Badalona, Spain.
10 Complejo Asistencial Universitario de Salamanca, Salamanca, Spain.
11 Hospital Universitario Ramón y Cajal, Madrid, Spain.
12 Hospital Universitario Virgen Macarena, Sevilla, Spain.
13 Hospital Arnau de Vilanova, Valencia, Spain.
14 MD Anderson Cancer Center, Madrid, Spain.
15 Hospital de Montecelo, Pontevedra, Spain.
16 Hospital Universitario Infanta Leonor, Universidad Complutense de Madrid, Madrid, Spain.
17 Hospital Xeral Cies, Vigo, Spain.
18 Hospital Virgen de la Luz, Cuenca, Spain.
19 Fundación Jiménez Díaz, Madrid, Spain.
20 Vivia Biotech, Tres Cantos, Madrid, Spain.
21 Specialized Hospital for Active Treatment of Hematological Diseases, Sofía, Bulgaria.
| This is an Open Access article distributed
under the terms of the Creative Commons Attribution License
(https://creativecommons.org/licenses/by-nc/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Induction schedules in acute myeloid leukemia (AML) are based on
combinations of cytarabine and anthracyclines. The choice of the
anthracycline employed has been widely studied in multiple clinical
trials showing similar complete remission rates.
Patients and Methods
|Table 1. Baseline characteristics of the 198 analyzed patients.|
|Figure 1. Average and Individual Dose Responses ex vivo for AML Drugs. Dose-Response Analysis was Completed for 3 Anthracyclines in Bone Marrow Samples From Patients With Acute Myeloid Leukemia; 227 with Idarubicin, 212 with Mitoxantrone and 271 with Daunorubicin. The Survival Index (y-Axis) Ranges From 100% to 0%, Displaying the Selective Acute Myeloid Leukemia Cell Depletion Calculated With Population Models. The Gray Lines Display Each Individual Response, With the Median Response Shown in yellow for Idarubicin, Panel (A); in blue for Mitoxantrone, Panel (B); and in red for Daunorubicin, Panel (C).|
|Table 2. Estimates of the ex vivo population pharmacodynamic parameters. Parameters typical and random (variability and residual error percentage) are shown together with the corresponding relative standard error calculated as the ratio between the standard error provided by NONMEM and the estimate. Estimates of inter-patient variability (IPV) are expressed as coefficient of variation (%).|
|Figure 2. Example of differential individual sensitivities to anthracyclines. Dotted lines represented individual response to each drug and cotinuous lines the median response to each drug. Panel (A) shows an example of a patient resistant to Idarubicin (right shifted dose response curve) but sensitive to Mitoxantrone (left shifted dose response curve). Panel (B) shows an example of a patient resistant to Idarubicin and Daunorubicin (right shifted dose response curve). Panel (C ) shows an example of a patient resistant to Daunorubicin (right shifted dose response curve) but sensitive to Mitoxantrone (left shifted dose response curve).|
|Figure 3. Comparison of the potency between anthracyclines. Panels A-C represented the pairwise comparisons between Area Under (AUC) the Dose-Response Curve of the anthracyclines, with their bisectors, linear regression lines and R2 values. Red dots represent patient samples with a difference in potency between these drugs greater than 30%. Panel (A) comparison between AUCs of Idarubicin and Mitoxantrone; Panel (B) comparison between AUCs of Daunorubicin and Mitoxantrone; Panel (C) comparison between AUCs of Daunorubicin and Idarubicin.|
|Table 3. Differences in Area Under the Dose-Response Curve between anthracyclines.|
|Figure 4. Differences in Area Under the Dose-Response Curve between anthracyclines. A 28.3% of patients samples showed >30% different potency among Idarubicin-Daunorubicin-Mitoxantrone Area Under the Dose-Response Curve (AUC).|
|Figure 5. Comparison of the potency between combinations of cytarabine and anthracyclines. Panels A-C represented the pairwise comparisons between Volume Under the Surface (VUS) of the combinations of cytarabine (CYT) with anthracyclines, with their bisectors, linear regression lines and R2 values. Red dots represent patient samples with a difference in potency between these drugs greater than 30%. Panel (A) comparison between VUS of Cytarabine + Mitoxantrone (CYT+MIT) and Cytarabine + Idarubicin (CYT+IDA); Panel (B) comparison between VUS of CYT+MIT and Cytarabine + Daunorubicin (CYT+DNR); Panel (C) comparison between VUS of CYT+DNR and CYT+IDA.|
|Figure 6. Differences in Volume Under the Surface between combinations of cytarabine and different anthracyclines. An 8.2 % of patients samples obtained >30% of different sensitivity in Volume Under the Surface (VUS) of Cytarabine + Idarubicin (CYT+IDA), Cytarabine + Daunorubicin (CYT+DNR) and Cytarabine + Mitoxantrone (CYT+MIT).|
|Table 4. Differences in Volume Under the Surface (VUS) between the combinations of cytarabine and different anthracyclines.|