| Literature DB >> 29296240 |
Hongliang Zhang1,2, Xiaobin Zhong2, Zhenguang Huang1, Chun Huang1, Taotao Liu1, Yue Qiu1.
Abstract
The effect of sulfonylurea for the treatment of neonatal diabetes (NDM) is remain uncertain. We conducted this systematic review and meta-analysis to investigate the effect of sulfonylurea for NDM and to provide the latest and most convincing evidence for developing clinical practice guidelines of NDM. A literature review was performed to identify all published studies reporting the sulfonylurea on the treatment of neonatal diabetes. The search included the following databases: PUBMED, EMBASE and the Cochrane Library. The primary outcome was the success rates of treatment, change of glycosylated hemoglobin (HbA1c) and C-peptide. Data results were pooled by using MetaAnalyst with a random-effects model. Ten studies (6 cohort studies and 4 cross-sectional studies) involving 285 participants were included in the analysis. The pooled estimated success rate by the random-effects model was 90.1%(95% CI: 85.1%-93.5%). HbA1c had a significantly lower compared with before treatment. The pooled estimate of MD was -2.289, and the 95% CI was -2.790 to -1.789 (P < 0.001). The subgroup analysis showed a similar result for cohort studies and in cross-sectional studies. The common mild side effect is gastrointestinal reaction. The present meta-analysis suggested that sulfonylurea had a positive effect for treatment NDM due to KATP channel mutations. In addition, sulfonylurea also displayed sound safety except the mild gastrointestinal reaction. However, the findings rely chiefly on data from observational studies. Further well-conducted trials are required to assess sulfonylurea for NDM.Entities:
Keywords: meta-analysis; neonatal diabetes; sulfonylurea; systematic review
Year: 2017 PMID: 29296240 PMCID: PMC5746142 DOI: 10.18632/oncotarget.22548
Source DB: PubMed Journal: Oncotarget ISSN: 1949-2553
Figure 1Selection process for the studies included in the meta-analysis
Search strategy
| #11 | Search #10 AND #3 | 395 |
| #10 | Search #6 AND #9 | 14766 |
| #9 | Search #7 OR #8 | 520111 |
| #8 | Search Diabetes [Title/Abstract] | 411384 |
| #7 | Search “Diabetes Mellitus” [Mesh] | 353111 |
| #6 | Search #4 OR #5 | 667779 |
| #5 | Search (neonatal [Title/Abstract]) OR Newborn [Title/Abstract] | 273607 |
| #4 | Search “Infant, Newborn” [Mesh] | 539228 |
| #3 | Search #1 OR #2 | 22050 |
| #2 | Search (((((((((glimepiride [Title/Abstract]) OR Acetohexamide [Title/Abstract]) OR Carbutamide [Title/Abstract]) OR Chlorpropamide [Title/Abstract]) OR Gliclazide[Title/Abstract]) OR Glipizide [Title/Abstract]) OR Glyburide [Title/Abstract]) OR Tolazamide [Title/Abstract]) OR Tolbutamide [Title/Abstract]) OR Sulfonylurea [Title/Abstract] | 13505 |
| #1 | Search “Sulfonylurea Compounds” [Mesh] | 17797 |
| #10 | #3 AND #6 AND #9 | 556 |
| #9 | #7 OR #8 | 849821 |
| #8 | diabetes:ab,ti | 586257 |
| #7 | ‘diabetes mellitus’/exp | 761547 |
| #6 | #4 OR #5 | 661321 |
| #5 | neonatal:ab,ti OR newborn:ab,ti | 322871 |
| #4 | ‘newborn’/exp | 518403 |
| #3 | #1 OR #2 | 26280 |
| #2 | sulfonylurea:ab, ti OR glyburide:ab,ti OR glipizide:ab, ti OR gliclazide:ab, ti OR glimepiride:ab, ti OR acetohexamide:ab, ti OR carbutamide:ab, ti ORchlorpropamide:ab, ti OR tolazamide:ab, ti OR tolbutamide:ab, ti | 17822 |
| #1 | ‘sulfonylurea’/exp | 11821 |
Characteristics of included studies
| Study | Country | Study design | Participants (KCNJ11/ABCC8 mutant) | Transfer sulfonylurea therapy | Successful treatment | Treatment regimen | Treatment time | Outcome indicators |
|---|---|---|---|---|---|---|---|---|
| Ewan R. Pearson 2006 [ | UK | cohort study | 49 | 49 | 44 | glibenclamide | 12 weeks | HbA1c |
| Juraj Stanik 2007 [ | Slovakia | cross-sectional study | 5 | 5 | 4 | glibenclamide | 1 month; 6 months | HbA1c, CGMS, C-peptide |
| Meena Rafiq 2008 [ | UK | cohort study | 27 | 27 | 23 | glibenclamide | HbA1c | |
| Jahnavi S 2013 [ | India | cross-sectional study | 10 | 5 | 5 | glibenclamide | HbA1c, glucose tolerant | |
| David Carmody 2014 [ | USA | cross-sectional study | 73 | 73 | 69 | glibenclamide | ||
| Brian W. Thurber 2015 [ | USA | cohort study | 58 | 58 | 58 | glibenclamide | HbA1c | |
| Jacques Beltrand 2015 [ | France | cohort study | 18 | 18 | 18 | glibenclamide | HbA1c, C-peptide | |
| Evgenia Globa 2015 [ | Ukraine | cross-sectional study | 12 | 12 | 11 | glibenclamide | 3 months; 1 year | HbA1c |
| Patricia Taberner 2016 [ | Argentina | Wcohort study | 8 | 5 | 4 | glibenclamide | 3 months | HbA1c, C-peptide |
| Yukiko Hashimoto 2016 [ | Japan | cohort study | 25 | 17 | 14 | glibenclamide | HbA1c, C-peptide |
Outcome data of included studies
| Study | HbA1c | Basal C-peptide, ng/mL | ||
|---|---|---|---|---|
| Before treatment | After treatment | Before treatment | After treatment | |
| Ewan R. Pearson 2006 [ | 8.1 (7.7–8.6) | 6.4 (6.2–6.6) | – | – |
| Juraj Stanik 2007 [ | 10.0 ± 0.73 | 6.2 ± 0.37 | 0.04 ± 0.04 | 0.73 ± 0.07 |
| Meena Rafiq 2008 [ | 7.2 (6.6–8.2) | 5.5 (5.3–6.2) | – | – |
| Jahnavi S 2013 [ | 10.18 ± 2.6 | 6.84 ± 0.46 | – | – |
| David Carmody 2014 [ | – | – | – | – |
| Brian W. Thurber 2015 [ | 8.5 ± 1.8 | 6.2 ± 1.0 | – | – |
| Jacques Beltrand 2015 [ | 7.75 (5.5–12.8) | 6.4 (5.4–10) | 0.07 (0.02–0.51) | 0.28 (0.12–0.82) |
| Evgenia Globa 2015 [ | 7.4 (6.6–9.6) | 5.6 (5.4–5.9) | – | – |
| Patricia Taberner 2016 [ | 8.56 ± 0.56 | 5.80 ± 1.07 | 0.15 ± 0.10 | 1.29 ± 0.97 |
| Yukiko Hashimoto 2016 [ | – | 6.4(4.9–8.5) | – | – |
NOS quality assessment of included cohort studies
| Items | Study | Ewan R. Pearson 2006 | Meena Rafiq 2008 | Brian W. Thurber 2015 | Jacques Beltrand 2015 | Patricia Taberner 2016 | Yukiko Hashimoto 2016 |
|---|---|---|---|---|---|---|---|
| Selection | Representativeness of the exposed cohort | ★ | ★ | ★ | ★ | ★ | ★ |
| Selection of the non-exposed cohort | ★ | ★ | ★ | ★ | ★ | ★ | |
| Ascertainment of exposure | ★ | ★ | ★ | ★ | ★ | ★ | |
| Demonstration that outcome of interest was not present at start of study | ★ | ★ | ★ | ★ | ★ | ★ | |
| Comparability | Comparability of cohorts on the basis of the design or analysis | ★★ | ★★ | ★★ | ★★ | ★★ | ★★ |
| Outcome | Assessment of outcome | ★ | ★ | ★ | ★ | ★ | ★ |
| Was follow-up long enough for outcomes to occur | ★ | – | ★ | ★ | ★ | ★ | |
| Adequacy of follow up of cohorts | ★ | ★ | ★ | ★ | ★ | ★ | |
| 9 | 8 | 9 | 9 | 9 | 9 | ||
Figure 2Forest plot of meta-analysis on treatment success rate
Figure 3Funnel plot of subgroup analysis on treatment success rate
Figure 4Forest plot of meta-analysis on changes of HbA1c level
Figure 5Forest plot of subgroup analysis on changes of HbA1c level
Figure 6Funnel plot of meta-analysis on treatment success rate
Figure 7Funnel plot of meta-analysis on changes of HbA1c level
AHRQ quality assessment of included cross-sectional studies
| Study | Juraj Stanik 2007 | Jahnavi S 2013 | David Carmody 2014 | Evgenia Globa 2015 | |
|---|---|---|---|---|---|
| Items | 1 | YES | YES | YES | YES |
| 2 | YES | YES | YES | YES | |
| 3 | YES | UNCLEAR | UNCLEAR | YES | |
| 4 | YES | YES | YES | YES | |
| 5 | UNCLEAR | UNCLEAR | UNCLEAR | UNCLEAR | |
| 6 | YES | YES | YES | YES | |
| 7 | YES | NO | UNCLEAR | UNCLEAR | |
| 8 | UNCLEAR | UNCLEAR | UNCLEAR | UNCLEAR | |
| 9 | UNCLEAR | UNCLEAR | UNCLEAR | UNCLEAR | |
| 10 | UNCLEAR | YES | YES | YES | |
| 11 | YES | NO | UNCLEAR | UNCLEAR | |
| 7 | 5 | 5 | 6 | ||