I have question regarding survival analysis. I am looking at observational studies comparing survival patients who received treatments A or B at different centres (>10), for the same condition and have been followed-up for different time periods (between 1 and 10 years). I have the duration of follow-up for all participants (or time to death), as well as data for some covariates.

I am wondering what the best way to compare the effect of treatments A and B on survival. My current plan was to attempt an analysis pooling the log hazard ratios/standard errors of the Cox model for each centre, as often done with other meta-analyses.

1. Is it an issue that there are quite a lot of varying ratios of participants receiving treatment A or B depending on the centre (these are observational studies), varying sample sizes and that the follow up periods vary by centre, particularly when combining all centres?

2. The Cox regression model assumes proportional hazards, but most likely adverse effects of the treatment would occur in the first year. Is there a way to account for this in the model, or elsewhere? I understand the Cox regression would consider survival across the entire follow-up period, but would it be worth, for this reason, to compare survival at 1 year as well?

3. I suppose this approach would be superior to simply indiscriminately pooling all participants and running a singular Cox regression on it, due to centre-specific biases and population/selection biases. Is there a way I could estimate this bias to see whether it actually exists (in case that the demographics are all comparatively similar between centres/groups)?

Thank you!

I have question regarding survival analysis. I am looking at observational studies comparing patient survival who received treatments A or B at different centres (>10), for the same condition and have been followed-up for different time periods (between 1 and 10 years). I have the duration of follow-up for all participants (or time to death), as well as data for some covariates.

I am wondering what the best way to compare the effect of treatments A and B on survival. My current plan was to attempt an analysis pooling the log hazard ratios/standard errors of the Cox model for each centre, as often done with other meta-analyses.

1. Is it an issue that there are quite a lot of varying ratios of participants receiving treatment A or B depending on the centre (these are observational studies), varying sample sizes and that the follow up periods vary by centre, particularly when combining all centres? Or is there a better analysis strategy?

2. The Cox regression model assumes proportional hazards, but most likely adverse effects of the treatment would occur in the first year. Is there a way to account for this in the model, or elsewhere? I understand the Cox regression would consider survival across the entire follow-up period, but would it be worth, for this reason, to compare survival at 1 year as well?

3. I suppose this approach would be superior to simply indiscriminately pooling all participants and running a singular Cox regression on it, due to centre-specific biases (given the treatment is surgical) and population/selection biases. Is there a way I could estimate this bias to see whether it actually exists (in case that the demographics are all comparatively similar between centres/groups)?

Thank you!