A Social Network Scrum Framework for Software Development under COVID-19 Pandemic

This research proposes a framework for social network scrum meeting that serves as an alternate means for work continuation under the COVID-19 pandemic. Conventional agile and scrum methods that require in-person meeting on daily basis, as well as scrum process become impractical under stringent ‘social lockdown’ mandates. To prevent any disruptive discontinuity, the proposed framework sets up an online meeting to replace the in-person stand-up meeting and scrum. Some supporting practices are also established to adjust both agile and scrum event flows that suit this online encounter. They are production development setup and social network meeting. The former offers industrial practices that are well entrenched and proven, while the latter has been used extensively in this digital age. The proposed method is tested with computer science student’s projects. Students are able to continue their meeting, discussion, and some outputs rather than being isolated with no fruitful outcome. The proposed method does establish some ground work to be explored for future software development environments that will suit to the imminent digital technological advancement.

Composite grading algorithm for National Cancer Institute’s PRO-CTCAE.

7018 Background: Standard reporting of symptomatic adverse events (AEs) in oncology relies on clinicians to rate patient (pt) experience using CTCAE; each symptom is represented by a single graded item. To capture direct pt experience, NCI developed PRO-CTCAE to supplement CTCAE. In PRO-CTCAE, the pt answers up to 3 questions per AE about a symptom’s frequency, severity and interference with daily activities. To align PRO-CTCAE with CTCAE, we developed an algorithm for mapping sets of questions for an AE to a single composite numerical grade. Methods: We used a 5-step process. (1) All 187 possible PRO-CTCAE score permutations were presented to clinical investigators to subjectively map permutations to single numerical grades (range 0-3). (2) Permutations with < 75% agreement were presented to investigator committees at a National Clinical Trials Network meeting to gain majority consensus via anonymous voting. (3) The resulting algorithm was refined via graphical and tabular approaches to assure directional consistency. (4) Validity, reliability and sensitivity were assessed in a national study dataset. (5) Accuracy for delineating AEs between study arms was measured in 2 phase III clinical trials (Alliance for Clinical Trials in Oncology A091105 and Exelixis COMET-2). Results: (1) 12/187 score permutations had < 75% initial agreement. (2) Majority consensus was reached for all permutations. (3) 5 mappings were adjusted to assure directional consistency. (4) Composite grades for 46/59 (78%) AEs were higher in pts with ECOG performance status 2-4 vs 0-1 (median effect size 0.23 [range -0.49-0.73]; 32/59 effect size ≥0.2; 25/59 p< 0.05), similar to when conducting analysis on individual unmapped items. The test-retest reliability for 24 selected composite grades ranged from 0.57-0.96 (median intraclass correlation coefficient [ICC] 0.77) with 18/24 (75%) grades having ICC ≥0.7. Median (range) standardized response means in pts reporting worsening, no change, and improvement were 0.20 (0.03-0.34), -0.06 (-0.20-0.03) and -0.12 (-0.32-0.06). (5) Pattern, directionality and statistical significance of between-arm differences in both trials were preserved with composite grades as compared to individual unmapped items. Conclusions: A composite grading algorithm for PRO-CTCAE was rigorously developed and validated. PRO-CTCAE composite grades may be useful in analyses to provide a single metric for each pt-reported AE for trial and real-world reporting. Support: UG1CA189823; U01CA233046; HHSN261200800043C; Bayer (A091105); https://acknowledgments.alliancefound.org .