Evaluation the effectiveness of the Curcumin as add-on to dienogest in patients with endometriosis.

Evaluation the effectiveness of the Curcumin as add-on to dienogest in patients with endometriosis

After collecting the data, in the first stage, basic clinical and demographic variables will be compared in the intervention and control groups. To compare the mentioned variables, independent t-test, chi-square and Fisher's exact test are used according to the type of variable and the assumptions of the mentioned tests. The method of analysis in this study will be analysis by intention to treat. Multiple imputation method will be used to estimate the missing data. In order to analyze the primary and secondary outcomes of the study, the mixed-effects linear regression statistical test will be used. The results will be calculated and reported as adjusted mean difference with 95% confidence. The variables included in the model include all the variables affecting the outcome, which have been proven in the literature review. A significance level of 0.05 will be considered in all tests. Stata statistical software version 16 will be used for data analysis.

All women referred to Ali Bin Abi Taleb (AS) Zahedan Hospital diagnosed with endometriosis and candidates for the prescription of Dingest without previous history of taking hormonal agents.

Women aged 18 to 45 with pain related to endometriosis proven by sonography and examination and history and candidates to receive Dynogest and without previous history of taking hormonal agents.

Curcumin and dienogest

1-the pain 2- Endometrioma size 3- Quality of Life 4- sexual function 5- Housing consumption

Sample size is 86 people, of which 43 people will be placed in each group. The block random allocation method was designed by an epidemiologist using WWW.Sealedenvelop.com. The number of considered blocks is 6.

The list of random allocation of patients will only be at the disposal of the plan's epidemiologist. In order to hide the random allocation process, random 10-digit codes are written on 86 paper labels without a specific order and framework, which is the identification number of the relevant treatment and only the project methodologist will be aware of the relevant code. The labels will be stuck on the medicine packages in the order of the randomization list. Medicine packages will be arranged in the order of the randomization list inside the box. When the doctor declares the eligibility of a patient, the methodologist will provide the patient with the package treatment plan. The person evaluating the intended outcomes is a third person who is unaware of the randomization process and the type of treatment performed. In order to analyze the data, a statistician who is separate from the study process and is unaware of all the processes will be used. The list of random allocation of patients will only be at the disposal of the plan's epidemiologist. In order to hide the random allocation process, random 10-digit codes are written on 86 paper labels without a specific order and framework, which is the identification number of the relevant treatment and only the project methodologist will be aware of the relevant code. The labels will be stuck on the medicine packages in the order of the randomization list. Medicine packages will be arranged in the order of the randomization list inside the box. When the doctor declares the eligibility of a patient, the methodologist will provide the patient with the package treatment plan. The person evaluating the intended outcomes is a third person who is unaware of the randomization process and the type of treatment performed. In order to analyze the data, a statistician who is separate from the study process and is unaware of all the processes will be used.