Unanchored indirect comparisons of interval censored outcomes like progression-free-survival (PFS) can be biased if progressions are assessed at different times across trials. Even a two-week difference can introduce bias when PFS is common at the first visit. Assessment schedule matching (ASM) adjusts for this bias using patient-level data from one of the trials (index) and adjusting progression times at the first two visits (e.g., week 6 (W6) and 12) to match the first assessment time of the comparator (e.g., W8). ASM creates a pseudo W8 visit in the index trial by: 1) Shifting progressions observed at W6 to W8 unless patients had died (which advances their PFS time) or their follow-up ended prior to W8 (which censors PFS at that time); 2) Since some progressions at W12 would have been observed at W8, some proportion (p) of events at W12 is shifted back to W8. p can be estimated from the proportion not progressed at weeks 6, 8 and 12 predicted from a parametric curve fitted to the observed time to progression (TTP) data in the index trial. Alternatively, p can be derived from an exponential distribution fitted to TTP within the period between weeks 6 and 12. Simulations assessed the two approaches in scenarios created to reflect differing degree of bias (8-11% in naïve analyses). ASM was equally effective with either approach, reducing the bias to below 1%. ASM can, therefore, be applied reliably with the simpler piecewise exponential-based approach, avoiding the additional step of parametric fitting for TTP, and possible distortions due to poor fit of the chosen distribution.