| Issue Number | 444 |
|---|---|
| Summary | [Literature] Remove Two Exclusion Reasons |
| Created | 2017-06-07 17:05:02 |
| Issue Type | Improvement |
| Submitted By | Juthe, Robin (NIH/NCI) [E] |
| Assigned To | Kline, Bob (NIH/NCI) [C] |
| Status | Closed |
| Resolved | 2017-06-14 09:48:19 |
| Resolution | Fixed |
| Path | /home/bkline/backups/jira/oceebms/issue.209788 |
We would like to remove the following exclusion reasons from the list:
-Already cited in the PDQ summary
-Missing/incomplete outcome data; major protocol deviations
Do these need to be mapped to current values? If so, both should be mapped to Other.
The approach we have take to pruning the list in the past is to mark the values we no longer want to show up on the reviewer's page as inactive (there's a column for that in the values control table) and to leave the existing uses of the values being retired in place, so we don't lose any information (see OCEEBMS-323). Is there a compelling reason for not using that same approach for these two value?
For reference, here are the usage counts for each of the reasons on DEV:
SELECT COUNT(*), v.value_name
FROM ebms_review_rejection_reason r
JOIN ebms_review_rejection_value v
ON v.value_id = r.value_id
GROUP BY v.value_name
ORDER BY 1;
+----------+--------------------------------------------------------------------------------+
| COUNT(*) | value_name |
+----------+--------------------------------------------------------------------------------+
| 2 | Randomized trial with flawed or insufficiently described randomization process |
| 10 | Conflict of interest |
| 14 | Missing/incomplete outcome data; major protocol deviations |
| 16 | Inappropriate interpretation of subgroup analyses |
| 22 | Inappropriate statistical analysis |
| 28 | Inadequate follow-up |
| 50 | Unvalidated outcome measure(s) used |
| 98 | Inappropriate study design or analyses |
| 179 | Already cited in the PDQ summary |
| 548 | Review/expert opinion/commentary |
| 727 | Inadequate study population |
| 899 | Other |
| 901 | Findings not clinically important |
| 1071 | Not relevant to the PDQ summary topic |
| 2169 | Preliminary findings; need confirmation |
| 2210 | Provides no new information/novel findings |
+----------+--------------------------------------------------------------------------------+
16 rows in set (0.02 sec)and here are the results from the same query on PROD:
+----------+--------------------------------------------------------------------------------+
| COUNT(*) | value_name |
+----------+--------------------------------------------------------------------------------+
| 3 | Randomized trial with flawed or insufficiently described randomization process |
| 12 | Conflict of interest |
| 22 | Inappropriate interpretation of subgroup analyses |
| 22 | Missing/incomplete outcome data; major protocol deviations |
| 31 | Inappropriate statistical analysis |
| 51 | Inadequate follow-up |
| 62 | Unvalidated outcome measure(s) used |
| 242 | Already cited in the PDQ summary |
| 254 | Inappropriate study design or analyses |
| 997 | Review/expert opinion/commentary |
| 1141 | Other |
| 1266 | Inadequate study population |
| 1431 | Findings not clinically important |
| 1601 | Not relevant to the PDQ summary topic |
| 3690 | Preliminary findings; need confirmation |
| 3775 | Provides no new information/novel findings |
+----------+--------------------------------------------------------------------------------+
16 rows in set (0.07 sec)Yes, that approach makes sense to me. Thanks.
Script installed and run on DEV.
Verified on DEV.
Verified on QA.
Verified on PROD.
Elapsed: 0:00:00.000684