What is PROsetta Stone?

Numerous patient-reported outcome (PRO) measures have been developed to assess similar health concepts. Typically, scores between measures cannot be compared.

PROsetta Stone provides tables that convert scores between two different measures.

PROsetta Stone tables enable clinicians and investigators to:

·       Synthesize research findings that utilize different measures

·       Easily transition between measures in clinical practice

·       Map known clinical score cut points from one measure to another

The PRO Rosetta Stone (PROsetta Stone®) developed and applied methods to link the Patient-Reported Outcomes Measurement Information System (PROMIS) with other related measures (e.g., SF-36, Brief Pain Inventory, CES-D, MASQ, FACIT-Fatigue) to expand the range of PRO assessment options within a common, standardized metric. The resulting tables provide equivalent scores between PROMIS and other scales that measure the same health concept. 

 

How to Use a PROsetta Stone Table

1. Score the non-PROMIS measure using the standard scoring conventions for the measure. For example, for the PHQ-9, sum raw scores on all items to produce a total score.

2. Find the PROsetta Stone table that includes the non-PROMIS measure (e.g., PROMIS Depression and PHQ-9 Linking Table).

3. Find your non-PROMIS measure score in the table and “walk across” to identify its corresponding PROMIS score. For example, a PHQ-9 = 18 total score corresponds to a PROMIS Depression T-score = 69.2 (SE = 3.2).

4. Calculate a confidence interval if desired. The formula for a 95% CI, is T-score + (1.96*SE). In this example, a PHQ-9 score of 18 is approximately equivalent to a PROMIS Depression T-score of 69.2 with a 95% CI of (62.9,75.4). This means that there is a 95% probability that a PHQ-9 score of 18 corresponds to a PROMIS Depression T-score between 62.9 and 75.4. Confidence intervals facilitate the interpretation of T-score precision.

5. Repeat steps 1-3 (and 4 if desired) for every score in your dataset. We do not recommend converting only the mean score of the non-PROMIS measure in your dataset when the individual patient-level scores are available.

6. Report summary statistics (such as mean and SD) on the newly converted PROMIS metric when writing scientific reports, but be sure to name the original non-PROMIS measure, the PROSetta Stone table used, and the associated publication, if applicable.

In some cases, the direction of scores between two measures is reversed (e.g., high scores are good on one measure and bad on another measure). You do not need to change the direction of scores; the tables take these directional differences into account. Each report has a paragraph that clarifies the score direction of each measure.

 

Featured Updates

New Publications

 

To learn more, contact: Help@HealthMeasures.net