Dear [Cochrane Collaborator/Expert],

 

I hope this message finds you well. My name is Wael, and I recently completed my MSc in Endocrinology. Currently, I am working on a network meta-analysis that compares the effectiveness of Liraglutide, Semaglutide, and Tirzepatide in individuals with obesity/overweight but without diabetes. I conducted this analysis as part of the requirements for my MSc and am now reaching out to seek your expertise to make significant revisions before submitting it for publication.

 

Background:

In the initial stages, my research did not specifically target Cochrane, and I focused on literature searches in MEDLINE and EMBASE. Recognizing the importance of a more comprehensive approach, I am now eager to extend the search to the Cochrane Database for a more thorough analysis.

 

Literature Search:

I kindly request your guidance on refining the search strategy and identifying relevant studies within the Cochrane Database to complement the information obtained from MEDLINE and EMBASE.

 

Data Extraction:

During the data extraction step, I encountered challenges understanding the differences between treatment regimen estimand and in-trial estimand tables. I am uncertain about which table is more suitable for data extraction and would greatly appreciate your insights on this matter.

 

Risk of Bias Assessment:

The risk of bias assessment is a critical aspect of my project that I believe requires substantial revision to enhance its robustness. I seek your expertise to ensure a comprehensive and accurate evaluation of study quality.

 

Network Meta-Analysis:

Acknowledging the complexities associated with network meta-analysis, I initially conducted a subgroup pairwise meta-analysis due to time constraints. However, I am now keen to transition to a full network meta-analysis and require your support in navigating the assumptions, ranking, and robustness of evidence synthesis.

 

Timeline:

I am committed to completing the revisions within a month as I recently delved into the study of network meta-analysis. I am a hard worker and am keen to publish within this timeframe to maintain the novelty factor.

 

Your expertise is highly valued, and I am eager to collaborate with you to ensure the success of this project. Your availability for a discussion or any written guidance would be immensely beneficial.

 

Thank you for considering my request, and I am hopeful for the opportunity to benefit from your expertise.

 

Best Regards,

Wael

MSc in Endocrinology

 

Ideal Mentor Criteria for Network Meta-Analysis Collaboration: 1. Expertise in Network Meta-Analysis: Possesses advanced knowledge and expertise in network meta-analysis, demonstrated through a robust publication record and successful completion of similar projects. 2. Effective Mentoring and Guidance: Demonstrates a clear and patient mentoring approach, breaking down complex concepts into understandable steps. Willingness to guide the mentee through the entire network meta-analysis process, offering insights into methodologies, data interpretation, and result reporting. 3. Regular Virtual Meetings: Commits to regular virtual meetings to discuss progress, address questions, and provide guidance throughout the project. Maintains open communication channels to ensure a collaborative and supportive mentor-mentee relationship. 4. Flexible Time Commitment: Acknowledges the potential time constraints on both parties and is open to a flexible schedule that accommodates the mentee's learning needs. Clarifies expectations regarding time commitment, whether it be a continuous engagement or periodic check-ins. 5. Joint Authorship Agreement: Recognizes that the mentor's contributions will be acknowledged through joint authorship in publications resulting from the project. Values the collaborative nature of the work and understands that the mentee will be the first author, followed by the university supervisors and the mentor as the fourth author. 6. Alignment with Academic Goals: Aligns mentorship activities with the academic goals and objectives of the mentee, ensuring the project contributes to the latter's academic and professional development. 7. Ethical Conduct and Integrity: Ensures adherence to ethical research conduct and encourages transparent reporting of methods and results. Upholds the highest standards of academic integrity throughout the mentorship. 8. Feedback and Iterative Learning: Provides constructive feedback on the mentee's work, fostering a culture of continuous improvement. Encourages iterative learning and allows the mentee to actively contribute to the project. 9. Commitment to Academic Collaboration: Expresses a commitment to collaborate academically, leveraging the mentor's expertise to enhance the overall quality and impact of the research. Welcomes the opportunity to engage in scholarly discussions and co-authorship responsibilities. 10. Long-Term Relationship Building: Demonstrates a willingness to build a long-term professional relationship beyond the immediate project, supporting the mentee's growth and development in the field. These criteria aim to outline the expectations for an ideal mentor, ensuring a mutually beneficial collaboration that contributes to both the mentee's academic growth and the success of the network meta-analysis project.