That's great news! Odd: REDCap shows 125 records from UNMC. Perhaps something got left-over? Perhaps export the tumor report<https://redcap.gpcnetwork.org/redcap_v6.11.5/DataExport/index.php?pid=32&report_id=103> and find the mismatch?
I still find 117 subjects, not 119 as expected. So I expect you're still working on that. p.s. In case I wasn't clear to anyone else: the naaccr_prep.py method doesn't provide the EMR data, i.e. BMI and langauge. I just made an EMR report<https://redcap.gpcnetwork.org/redcap_v6.11.5/DataExport/index.php?pid=32&report_id=110>; it confirms that UNMC does supply these data. -- Dan ________________________________ From: [email protected] [[email protected]] on behalf of Pedersen, Jay G [[email protected]] Sent: Monday, October 31, 2016 3:27 PM To: [email protected] Subject: BC Survey -- UNMC update, using the most recent NAACCR record when multiple records exist for the same patient+tumor Hi, I just updated the UNMC BC Survey #2 tumor datamart in GPC RedCap. DETAILS We are using the naaccr_prep.py method of creating redcap data directly from the NAACCR input files. We had issues where multiple NAACCR records (from multiple files) would exist for the same tumor. We previously had 143 records in our tumor datamart CSV file, of which there were only 124 unique study-id:tumor-id values. I have since examined the records for all of our consented breast cancer patients, and where there was more than one record -- chose the the most recent record for the combined XVA file that I created. At that point, I was able to run naaccr_prep and get a tumor datamart CSV file with exactly 124 rows, for the 124 unique study-id:tumor-id values. Jay Pedersen, M.A. Department of Pathology/Microbiology UNMC The information in this e-mail may be privileged and confidential, intended only for the use of the addressee(s) above. Any unauthorized use or disclosure of this information is prohibited. If you have received this e-mail by mistake, please delete it and immediately contact the sender.
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