| Literature DB >> 35455413 |
Yeonhong Lee1,2, Eun Jeong Jang1, Ha-Young Yoon1, Jeong Yee1, Hye-Sun Gwak1.
Abstract
6-Mercaptopurine (6-MP) is a cornerstone of the maintenance regimen for pediatric acute lymphoblastic leukemia (ALL). Inosine triphosphate pyrophosphatase (ITPA) is considered a candidate pharmacogenetic marker that may affect metabolism and 6-MP-induced toxicities; however, the findings are inconsistent. Therefore, we attempted to evaluate the effect of ITPA 94C>A polymorphism on 6-MP-induced hematological toxicity and hepatotoxicity through a systematic review and meta-analysis. A literature search for qualifying studies was conducted using the PubMed, Web of Science, and Embase databases until October 2021. Overall, 10 eligible studies with 1072 pediatric ALL patients were included in this meta-analysis. The results indicated that ITPA 94C>A was significantly associated with 6-MP-induced neutropenia (OR 2.38, 95% CI: 1.56-3.62; p = 0.005) and hepatotoxicity (OR 1.98, 95% CI: 1.32-2.95; p = 0.0009); however, no significant association was found between the ITPA 94C>A variant and 6-MP-induced leukopenia (OR 1.75, 95% CI: 0.74-4.12; p = 0.20). This meta-analysis demonstrated that ITPA 94C>A polymorphism could affect 6-MP-induced toxicities. Our findings suggested that ITPA genotyping might help predict 6-MP-induced myelosuppression and hepatotoxicity.Entities:
Keywords: 6-mercaptopurine; ITPA 94C>A; adverse drug reactions; inosine triphosphate pyrophosphatase; polymorphism
Year: 2022 PMID: 35455413 PMCID: PMC9027773 DOI: 10.3390/ph15040416
Source DB: PubMed Journal: Pharmaceuticals (Basel) ISSN: 1424-8247
Figure 1PRISMA flow diagram for the meta-analysis.
Characteristics of studies included in the meta-analysis.
| Study | Country | Sample Size (Male %) | Age (Years) | 6-MP Dose | Dose Adjustment | Concomitant Drugs | Outcome | Genotyping Method | NOS Score |
|---|---|---|---|---|---|---|---|---|---|
| Azimi et al. (2015) [ | Iran | 70 (48.6) | 1–9 c | 50 mg/m2 | To maintain a WBC count of 2000–3000/μL | MTX | Leukopenia | Sanger method | 7 |
| Chiengthong et al. (2016) [ | Thailand | 82 (40.2) | 5.4 | 50 mg/m2 | To maintain ANC 500 -1500/μL | VCR, PD, MTX, IT MTX | ANC < 500/μL | Pyrosequencing | 6 |
| Jantararoungtong et al. (2021) [ | Thailand | 115 (54.8) | 6.11 ± 3.86 | 75 mg/m2 | To maintain WBC ≥ 1500/μL, ANC ≥ 500/μL ± infection records | Low risk: | Leukopenia: WBC < 2000/μL | TaqMan assays | 6 |
| Mao et al. (2021) [ | China | 149 (57.0) | 5.92 | 50 mg/m2 | To maintain a WBC count of 2000–3000/μL | MTX 20 mg/m2 PO weekly | Leukopenia: WBC < 2000/μL | Fluorescence in situ hybridization | 6 |
| Milosevic et al. (2018) [ | Serbia | 60 (55.9) | 5.2 | 50 mg/m2 | To maintain a WBC count of 2000–3000/μL | MTX 20 mg/m2 PO weekly | Hepatotoxicity: Elevated levels of transaminases | PCR-RELP method | 6 |
| Moradveisi et al. (Kurdistan) (2019) [ | Kurdistan | 74 (58.1) | 6.25 ± 3.07 | 75 mg/m2 | To maintain a WBC count of 2000–3000/μL, ANC > 500/μL | MTX 20 mg/m2 PO weekly | Febrile neutropenia: ANC < 1000/mm3 with a single temperature of >38.3 °C (101 °F) or a sustained temperature of ≥38 °C (100.4 °F) for more than one hour | PCR-RELP method | 6 |
| Moradveisi et al. (Lebanon) (2019) [ | Lebanon | 136 (56.6) | 6.63 ± 4.93 | 75 mg/m2 | To maintain a WBC count of 1500–3000/μL, ANC > 300/μL, PLT > 50,000 | MTX 40 mg/m2 PO weekly | Febrile neutropenia: ANC < 1000/mm3 with a single temperature of >38.3 °C (101 °F) or a sustained temperature of ≥38 °C (100.4 °F) for more than one hour | TaqMan allele | 6 |
| Rosalina et al. (2012) [ | Malaysia | 63 (52.3) | 10.13 | N/A | N/A | N/A | Liver toxicity | Allele-specific PCR | 6 |
| Stocco et al. (2009) [ | USA | 244 (58.6) | 5.9 | 75 mg/m2 | When patients developed toxicity attributable to 6-MP | Low risk: | Grade 3/4 febrile neutropenia | TaqMan assay | 8 |
| Tanaka et al. (2018) [ | Japan | 95 (49.5) | 4.9 | 40 mg/m2 | To maintain a WBC count of 2000–3500/μL | MTX 25 mg/m2 PO weekly | Leukopenia: WBC < 2000/μL or | TaqMan assays | 6 |
| Zaman et al. (2019) [ | Bangladesh | 75 (NA) | 5 ± 2.5 | 75 mg/m2 | When patients developed toxicity attributable to 6-MP | NA | Leukopenia: WBC < 3000/μL | TaqMan assays | 8 |
Ara-C: cytarabine; ALT: alanine aminotransferase; ANC: absolute neutrophil count; CP: cyclophosphamide; DEX: dexamethasone; IT: intrathecal; MTX: methotrexate; NA: not applicable; NOS: Newcastle-Ottawa scale; PCR: polymerase chain reaction; PD: prednisolone; RELF: restriction fragment length polymorphism; SD: standard deviation; ULN: upper limits of normal; VCR: vincristine; VP-16: etoposide; WBC: white blood cell a median (range), b mean (range), c range, d Week 1: VP-16 300 mg/m2 IV + CP 300 mg/m2, Week 2: MTX 40 mg/m2 IV + 6-MP 75 mg/m2 PO daily, Week 3: MTX 40 mg/m2 IV + Ara-C 300 mg/m2, Week 4: VCR 1.5 mg/m2 + Dex 8 mg/m2 daily, Week 5: VP-16 300 mg/m2 IV + CP 300 mg/m2, Week 6: MTX 2000 mg/m2 + 6-MP 75 mg/m2 PO daily, Week 7: VP-16 300 mg/m2 IV + CP 300 mg/m2, Week 8: VCR 1.5 mg/m2 +Dex 8 mg/m2/ daily.
Figure 2Forest plot of the association between ITPA 94C>A polymorphism and 6-MP-induced toxicities: (A) Neutropenia, (B) Leukopenia, and (C) Hepatotoxicity.
Sensitivity analysis of the association between ITPA 94C>A status and 6-MP induced toxicities by sequentially excluding each study (ITPA wild type vs ITPA variant).
| Study Excluded | Heterogeneity | Statistical Model | Odds Ratio (95% CI) |
|---|---|---|---|
| Neutropenia | |||
| None | 55 | Random | 2.60 (1.30–5.19) |
| Azimi et al. (2015) | 55 | Random | 2.27 (1.14–4.54) |
| Chiengthong et al. (2016) | 63 | Random | 2.87 (1.20–6.88) |
| Jantararoungtong et al. (2021) | 46 | Fixed | 3.07 (1.90–4.96) |
| Moradveisi et al. (2019) | 57 | Random | 2.36 (1.19–4.69) |
| Moradveisi et al. (2019) | 53 | Random | 3.11 (1.51–6.38) |
| Stocco et al. (2009) | 61 | Random | 2.57 (1.09–6.06) |
| Zaman et al. (2019) | 50 | Random | 2.16 (1.05–4.43) |
| Leukopenia | |||
| None | 70 | Random | 1.75 (0.74–4.12) |
| Azimi et al. (2015) | 69 | Random | 1.39 (0.61–3.16) |
| Jantararoungtong et al. (2021) | 77 | Random | 2.11 (0.67–6.71) |
| Mao et al. (2021) | 77 | Random | 1.97 (0.56–6.89) |
| Tanaka et al. (2018) | 58 | Random | 2.38 (1.02–5.52) |
| Zaman et al. (2019) | 64 | Random | 1.30 (0.56–3.03) |
| Hepatotoxicity | |||
| None | 41 | Fixed | 1.98 (1.32–2.95) |
| Azimi et al. (2015) | 0 | Fixed | 1.68 (1.10–2.58) |
| Jantararoungtong et al. (2021) | 34 | Fixed | 2.41 (1.53–3.80) |
| Mao et al. (2021) | 46 | Fixed | 1.37 (1.37–3.44) |
| Milosevic et al. (2018) | 46 | Fixed | 1.90 (1.26–2.85) |
| Moradveisi et al. (2019) | 49 | Fixed | 1.99 (1.33–2.98) |
| Moradveisi et al. (2019) | 48 | Fixed | 2.00 (1.33–3.01) |
| Rosalina et al. (2012) | 48 | Fixed | 2.05 (1.34–3.13) |
| Tanaka et al. (2018) | 48 | Fixed | 2.04 (1.34–3.12) |
| Zaman et al. (2019) | 36 | Fixed | 1.72 (1.11–2.66) |
Figure 3Funnel plot for publication bias of the included studies: (A) Neutropenia, (B) Leukopenia, and (C) Hepatotoxicity.