Maturity of survival data is a key consideration in the assessment of the value of oncology drugs based on clinical trial evidence. Where there is a hypothesis of a cure fraction or other sources of non-proportional hazards, understanding the quantity and quality of information within Kaplan-Meier tails becomes particularly important in the analysis and interpretation of survival data. Despite this there are limited metrics for and no clear standards applied to data maturity. We calculate indices of data completeness and sensitivity over time for combination therapies in relapsed or refractory multiple myeloma, to demonstrate concepts of data maturity that could be potentially useful. Kaplan-Meier curves for overall survival were sourced from pivotal study publications and published long-term follow-up data for combination therapies licensed by the EMA since 2015 for second-line treatment of multiple myeloma. We digitised survival curves and calculated indices for data completeness and sensitivity for five regimens: elotuzomab; carfilzomib in combination with lenalidomide and dexamethasone and with dexamethasone alone; daratumumab in combination with bortezomib and dexamethasone and with lenalidomide and dexamethasone. Plots of data completeness demonstrate substantial differences in the length of follow-up for which mature data is available. While both daratumumab regimens have generated strong hazard ratios, mature data is available for a much more limited period than other regimens. Plots of data sensitivity show noticeable declines in reliability of information beginning approximately 6 months prior to maximum follow-up for most regimens, with elotuzomab declines beginning somewhat earlier. Indices of data completeness and sensitivity are simple and visually appealing means of measuring and comparing survival data maturity. Use of these indices and development of consensus threshold values that can be applied to them can be a valuable tool in the comparative assessment of oncology therapies.