Evaluating the “Good Death” Concept from Iranian Bereaved Family

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DISTRIBUTION-BASED ANALYSIS The distribution-based estimates for the BPI-SF worst pain rating are presented in Table 5. There appears to be consistency with the 1 SEM estimates, the 0.50 effect size, and the 0.50 Guyatt’s statistic. INTEGRATING ANCHOR-BASED AND DISTRIBUTION-BASED MID ESTIMATES The distribution-based analyses suggest that the MDC for the worst pain rating, defined as the smallest change that can be reliably differentiated from random fluctuation, is between 1.3 and 1.6 points (see Table 5). This represents the lower bound for establishing the MID. The results from regression analyses can be used to translate changes between anchors and corresponding changes in BPI-SF worst pain. This strategy can be particularly informative when the MID for an anchor is known. This is the case for the EQ-5D Health State Index, where the MID has been estimated at 0.06 for U.S. Index scores and 0.07 for U.K. Index scores. 23 A one-point change in EQ-5D Index translates to a change of �3.548 in BPI-SF worst pain, so a 0.07-point change in EQ-5D Index (the MID for the measure) corresponds to a change of �0.248 in BPI-SF worst pain. In contrast, a one-point change in BPI-SF worst pain (which is smaller than the MID based upon the distributionbased analyses) translates to a change of 0.036 for the EQ-5D Index score (considerably smaller than the MID of 0.07). However, a two-point change in BPI-SF worst pain rating corresponds to a 0.072 change in EQ-5D Index score, which is almost identical to the MID for that measure. This suggests that a two-point change may be a reasonable estimate for the MID of the BPI-SF worst pain rating. Discussion Data from both distribution-based and anchor-based approaches were used to develop estimates of the MID for the BPI-SF worst pain rating. Results from these approaches are similar, providing reasonably strong support for establishing a two-point MID for the BPI-SF worst pain rating. Further, the results suggest that this estimate of MID is, for the most part, independent of baseline BPI-SF worst pain ratings. However, there is some evidence to suggest that the direction of change (improvement or worsening) may be important to consider. A number of reports have suggested that a smaller change may be required to be considered clinically important when a patient is improving compared with worsening. 13 Also, when considered as a percentage, a one-point change in any scale has a different value for an increase versus a decrease; eg, a change from 2 to 3 is an increase of 50%, while a change from 3 to 2 is a decrease of 33%. Nonetheless, these findings provide important information to researchers for interpreting changes in the BPI-SF worst pain ratings. In addition, although not specific to the BPI worst pain rating, the findings of this study are consistent with other Mathias et al published MID analyses for a similar item. A recent review of three studies concluded that, for a numerical rating scale of pain intensity ranging 0–10 similar in content to the BPI-SF worst pain rating, changes of around two points represent “meaningful,” “much better,” or “much improved” reductions in chronic pain. 24 Several factors contribute to the overall strength of the current results. First, as frequently recommended in the literature, 11 both anchor-based and distribution-based methods were used to estimate the MID for the worst pain rating. Second, analyses were based on a large sample, totaling over 1,500 patients for the baseline to week 25 assessment interval. A larger sample size will generally provide a broader distribution of responses, which will likely increase the generalizability of the results. Third, multiple anchors were used to evaluate changes in BPI-SF worst pain ratings. Fourth, analyses were performed across several assessment intervals to determine the strongest relationship between BPI-SF ratings and other anchors. Finally, the regression analyses provide important information about whether baseline differences influence the relationship between BPI-SF and other PRO measures. Nevertheless, these analyses are not without certain limitations. The sample for the current analyses consisted entirely of breast cancer patients. It is unclear to what extent these results will be relevant for other patient populations. Further research is needed to determine whether the MID for the BPI-SF worst pain rating established in this sample has broader applicability. Also, it must be noted that the recall period varied across assessments. The BPI-SF focuses on the past 24 hours, the FACT uses the past week, and the EQ-5D uses the present moment. It is unclear to what extent these differences in recall periods may have influenced the current results. Finally, the baseline to week 25 interval was used to determine the MID for the BPI-SF worst pain rating based on the higher correlations for this interval. Data from baseline to week 49 are consistent with these results, providing some confirmatory evidence to suggest that these MID estimates are stable. In conclusion, the findings of the present analyses suggest that the MID estimate for the BPI-SF worst pain rating is two points. This value provides guidance to researchers using the BPI-SF worst pain rating on how to interpret baseline differences as well as change scores in the BPI-SF worst pain rating. Additional analyses could be done in other populations to confirm these findings. Acknowledgments: The authors acknowledge the contributions of Betsy Tschosik, Health Outcomes Solutions, for assistance in the preparation of this manuscript and Vidya Setty of Amgen, Inc., for editing assistance. Conflicts of interest: This research was funded by Amgen Inc., Thousand Oaks, CA in part through a contract to Health Outcomes Solutions. SDM and RDC were paid by Health Outcomes Solutions, and YQ, QJ, RD and KC are employees of Amgen and own Amgen stock and stock options. VOLUME 9, NUMBER 1 � JANUARY/FEBRUARY 2011 www.SupportiveOncology.net 77
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