Review ArticleOpen Access

A Cross-Over Study to Evaluate the Effect of Glucagon-Like Peptide 1 on Women with Polycystic Ovarian Syndrome

Volume 1 - Issue 6

**Yu Liu¹, Suyan Tian², Ming-Wen An³ and Lu Wang⁴**

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- ¹Sir Run Run Hospital, Nanjing Medical University, Nanjing, Jiangsu, China
- ²Department of Endocrinology, Second Hospital of Jilin University, Changchun, Jilin, China
- ³Department of Mathematics, Vassar College, Poughkeepsie, New York, NY, USA
- ⁴Division of Clinical Research, First Hospital of Jilin University, Jilin, China
*Corresponding author: Yu Liu, Sir Run Hospital, Nanjing Medical University, 109 Longman Avenue, Nanjing, Jiangsu, China, 211166

*Corresponding author: Suyan Tian, Division of Clinical Research, First Hospital of Jilin University, 71 Xiamen Street, Changchun, Jilin, China

Received: November 08, 2017; Published: November 15, 2017

DOI: 10.26717/BJSTR.2017.01.000534

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Abstract

Background: Crossover design is very popular for a study of new and developmental drugs. However this design tends to be misused regardless of whether it is suitable for underlying research questions.

Method: Given that in clinical practice 2x2 cross over is the most commonly used design, the Hills- Arbitrage approach is suggested to analyze data. Furthermore, we propose fitting a linear mixed model and then conducting a likelihood ratio test to yield a single p-value on data with multiple time points within each stratum.

Finding: Applying these methods to a real data, we evaluate effect of glucagon-like peptide 1 (GLP-1) on women with polycystic ovarian syndrome (PCOS). Despite absence of statistically significant results, this study as the first study to explore direct administration of GLP-1 to PCOS women is nevertheless clinically meaningful. Not only does it show a longer washout period is desired, but also it suggests GLP-1 may have the same positive effect on PCOS as MET does.

Improvement: A larger parallel study is warranted, and clinicians and biostatisticians should collaborate more so that data can be analyzed appropriately and interpreted from both statistical and clinical points of view.

Keywords: Crossover Design; Longitudinal Data; Carryover Effect; The Hills-Arbitrage Approach; Polycystic Ovarian Syndrome (Pcos)

Abbreviations: LMM: Linear Mixed Effects Model; GEE: Generalized Estimation Equations; TG: Triglyceride; TC: Total Cholesterol; HDL: High-Density Lipoprotein; LDL: Low-Density Lipoprotein; FSH: Follicle-Stimulating Hormone; E: Estradiol; T: Testosterone; LH: Luteinizing Hormone; PRL: prolactin; OGTT: Oral Glucose Tolerance Test; IQR: Inter-quantile range