Weekly OHDSI Digest - 30Apr2018

MauraBeaton · April 30, 2018, 8:38pm

OHDSI MEETINGS THIS WEEK

OHDSI Community Call - Tuesday at 12pm ET
https://meetings.webex.com/collabs/#/meetings/detail?uuid=M59X2V1U61WC9ASID2Z5N3UT95-D1JL&rnd=811649.98682211121
US TOLL: +1-415-655-0001
Meeting Number: 199 982 907

GIS working group meeting - Next Monday (May 7th) at 10am ET

Meeting Number: 735 317 239
Password: gaia

ANNOUNCEMENTS

2018 OHDSI F2F this week! If you have any questions about the 2018 F2F please join tomorrow’s community or check out the F2F event page: https://www.ohdsi.org/events/2018-ohdsi-face-to-face/
If you are registered for the F2F you should be receiving regular emails with information about the event. If you registered but have not be receiving emails email beaton@ohdsi.org and let me know.

OHDSI Europe - Check out photos from the 2018 OHDSI European Symposium here: https://www.ohdsi.org/2018-european-symposium-photos/
Videos will be posted later this week!

2018 OHDSI Symposium - Collaborator showcase
Back by popular demand, the collaborator showcase will be part of the 2018 OHDSI Symposium, set to take place on October 12th at the Bethesda North Marriott! Once again we’ll be inviting collaborators to participate in the collaborator showcase by submitting abstracts to give poster presentations, software demonstrations or oral presentations. Our call for abstracts will open May 10th.

Reality is the leading cause of stress

Lily Tomlin

COMMUNITY PUBLICATIONS

Towards Patient-Driven Phenotyping and Similarity for Precision Medicine

CrowdED: Guideline for Optimal Crowdsourcing Experimental Design
https://dl.acm.org/citation.cfm?id=3191543

Comparing a Mobile Decision Support System Versus the Use of Printed Materials for the Implementation of an Evidence-Based Recommendation: Protocol for a Qualitative Evaluation

Impact of different assumptions on estimates of childhood diseases obtained from health care data: A retrospective cohort study.

ncbi.nlm.nih.gov

Impact of different assumptions on estimates of childhood diseases obtained from health care data: A retrospective cohort study.

OU Osokogu, A Pacurariu, M Mosseveld, P Rijnbeek, D Weibel, K Verhamme and MCJM Sturkenboom, Pharmacoepidemiology and drug safety, Jun 2018

Accurate estimates of disease incidence in children are required to support pediatric drug development. Analysis of electronic health care records (EHR) may yield such estimates but pediatric-specific methods are lacking. We aimed to understand the impact of assumptions regarding duration of disease episode and length of run-in period on incidence estimates from EHRs.Children aged 0 to 17 years (5-17 years for asthma) registered in the Integrated Primary Care Information database between 2002 and 2014 were studied. We tested the impact of the following: maximum duration of disease episode (0, 14, 30, 60, and 90 days) on recurrent diseases (acute otitis media [common] and acute pyelonephritis [rare]); and database run-in period on chronic diseases-asthma (common) and type 1 diabetes (DM) (rare). We calculated incidence rate ratios with 95% confidence intervals and stratified using 1-year age categories.Altogether, 503 495 children were registered. The incidence of acute otitis media was highest in <2-year-old children; using 30 days disease duration as reference, the rate increased with 8% if the duration was 14 days and decreased with 8% when extended to 60 days. Disease duration did not impact acute pyelonephritis (rare). No run-in (to exclude prevalent cases) versus 24-month run-in period overestimated the incidence rate for asthma and DM by a factor of 2.Analysis of EHR allows for estimation of disease incidence in children, but assumptions regarding episode length and run-in period impact the incidence estimates. Such assumptions may be routinely explored.

Lung dose and the potential risk of death in postoperative radiation therapy for non-small cell lung cancer: A study using the method of stratified grouping.

ncbi.nlm.nih.gov

Lung dose and the potential risk of death in postoperative radiation therapy for non-small cell lung cancer: A study using the method of stratified grouping.

J Heo, OK Noh, HI Kim, M Chun, O Cho, RW Park, D Yoon and YT Oh, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology, Oct 2018

Postoperative radiation therapy may have a detrimental effect on survival in patients with non-small cell lung cancer. We investigated the association of the lung radiation dose with the risk of death in patients treated with postoperative radiation therapy.We analyzed 178 patients with non-small cell lung cancer who received postoperative radiation therapy. The mean lung dose was calculated from dose-volume data, and we categorized patients into the high and low lung dose groups using 2 different methods; (1) simple grouping using the median lung dose of all patients, and (2) stratified grouping using the median lung dose of each subgroup sharing the same confounders. We compared clinical variables, and survival between the high and low lung dose groups.In the simple grouping, there were no significant differences in survivals between the high and low lung dose groups. After stratification, the overall survival of low lung dose group was significantly longer than that of high lung dose group (5-year survival, 60.1% vs. 35.3%, p = 0.039). On multivariable analyses, the lung dose remained a significant prognostic factor for overall survival (hazard ratio, HR = 2.08, p = 0.019).The lung dose was associated with the risk of death in patients with non-small cell lung cancer having the same confounders. Further studies evaluating the risk of death according to the lung dose will be helpful to administer more precise and individualized postoperative radiation therapy.