![The Japan Diabetes Society](/sites/default/files/inline-images/Diabetes_0.png)
Purpose
The purpose of this project was to understand the needs of Japanese researchers, to inform areas for new standards development to advance clinical research, and to expand collaboration between researchers in Japan and CDISC. This project was focused on reviewing the diabetes mellitus and associated chronic diseases Self-Management Item Sets (SMIS) identified by the Japanese Collaborative Committee for Clinical Informatization in Diabetes Mellitus (CCCIDM)1,2 and to assess how they map to existing CDISC standards.
Methodology
The project scope was to review the 43 items from the combined SMISs from diabetes mellitus, hypertension, dyslipidemia, and chronic kidney disease (CKD), assess how they map to existing CDISC Foundational Standards (i.e., Study Data Tabulation Model Implementation Guide (SDTMIG) v 3.43 and controlled terminology4), and to identify the gaps. In addition to SDTMIG v3.4 and controlled terminology, related Therapeutic Area User Guides (TAUGs) were utilized in the assessment, including:
- Diabetes Therapeutic Area User Guide v1.05
- Diabetes Type 1 Therapeutic Area User Guide - Screening, Staging and Monitoring of Pre-clinical Type 1 Diabetes6
- Diabetic Kidney Disease Therapeutic Area User Guide v1.07
- Dyslipidemia Therapeutic Area User Guide v1.08
- Polycystic Kidney Disease (PKD) Therapeutic Area User Guide v1.09
To ensure completeness of assessment, keyword searches for the 43 concepts were performed in CDISC’s Examples Collection10 and the CDISC wiki11 as additional resources.
Finally, each of the SMIS items were searched in the available CDISC Biomedical Concepts (BCs).12 Gaps were defined as SMIS items for which no SDTM example was found in the above resources, and/or for which the SDTM modeling strategy would require further discussion.
1 | Height | 22 | Serum albumin |
2 | Weight | 23 | Hematuria |
3 | Systolic blood pressure | 24 | Total cholesterol / Non-HDL-cholesterol |
4 | Diastolic blood pressure | 25 | Urine albumin/creatinine |
5 | LDL-cholesterol | 26 | AST |
6 | HDL-cholesterol | 27 | Waist |
7 | Smoking | 28 | Urine glucose |
8 | Serum creatinine | 29 | y-GTP |
9 | Urine protein | 30 | Diabetic neuropathy |
10 | Blood glucose | 31 | Regular visit at dental clinic |
11 | Age diagnosed as diabetes mellitus | 32 | Uric acid |
12 | HbA1c (NGSP) | 33 | Systolic blood pressure at home |
13 | ALT | 34 | Diastolic blood pressure at home |
14 | Diabetic retinopathy | 35 | Family history of renal failure |
15 | Age diagnosed as hypertension | 36 | Urine protein/creatinine |
16 | Serum potassium | 37 | Urine protein/Day |
17 | Abnormality on ECG | 38 | Serum total protein |
18 | Triglyceride | 39 | BUN |
19 | Age diagnosed as dyslipidemia | 40 | Hemoglobin |
20 | History of coronary disease | 41 | Cystatin C |
21 | Age diagnosed as CKD | Extra | Weight at home |
Extra | Self-monitoring blood glucose |
Table 1. The 43 combined items of the SMIS produced by the Collaborative Committee for Clinical Informatization in Diabetes Mellitus (CCCIDM)
Findings
Of the 43 data concepts reviewed, 31 were found to have no gaps with existing CDISC standards. These 31 concepts have pre-existing illustrative examples in various CDISC resources to support their modeling in SDTM, and/or controlled terminology for the core concept. For the items where only controlled terminology could be found, the mapping to SDTM is straightforward for users with prior knowledge of SDTM. Additionally, some of these 30 concepts would require minor adjustments to align with controlled terminology, such as adjusting the concept name, response options, or units.
The remaining 12 concepts would require additional discussion to determine how best to model in SDTM, but many of these appear to be close matches with existing concepts. Some of these items align well existing SDTM modeling with the addition of non-standard variables (e.g., age at onset of [any event)].
Finally, the search for the 43 SMIS items in the published CDISC Biomedical Concepts found 29 matches.
Discussion and Future Steps
It is important to note that the starting list of 43 data items from the SMIS was limited to the observation concept, response list, and associated units (where applicable). A complete SDTM record would contain additional qualifiers not informed by this starting list (e.g., laboratory methodology, subject position during assessment).
The availability of 29 of the SMIS items as CDISC BCs is encouraging. BCs reduce barriers to standards implementation by providing pre-configured value level metadata for the most used attributes associated with the concept. Providing the details necessary to create SDTM-conformant datasets, BCs also reduce variation in standards implementation across studies and investigators. Expansion of CDISC BCs to include the remaining 14 SMIS items is a recommended area of future expansion for this project.
Additional CDISC standards (e.g., ADaM) may also be an area for expansion, as well as looking at further item sets as identified by the project team. Reviewing data capture instruments such as Case Report Forms would make the gap analysis more complete.
Acknowledgements
This project was supported by the Japanese Ministry of Health, Labour and Welfare (MHLW) Research Grant (Number 23IA1016) obtained by Professor Naoki Nakashima.
Development activities have been done in collaboration with the Japanese Collaborative Committee of Clinical Informatization in Diabetes Mellitus, consisting of the Japan Diabetes Society, the Japanese Society of Hypertension, Japan Atherosclerosis Society, Japanese Society of Nephrology, Japanese Society of Laboratory Medicine, and Japan Association for Medical Informatics.
References
- Nakashima, et al: Recommended configuration for personal health records by standardized data item sets for diabetes mellitus and associated chronic diseases: A report from Collaborative Initiative by six Japanese Associations J Diabetes Investigation, 2019;10: 868–875.
- Naoki Nakashima, et al., Recommended configuration for personal health records by standardized data item sets for diabetes mellitus and associated chronic diseases: a report from a collaborative initiative by six Japanese associations,Diabetology International, 2019, 10(2):85–92
- Study Data Tabulation Model v3.4, Assessed May 16, 2024
- https://www.cdisc.org/standards/terminology, Accessed May 16, 2024
- Diabetes Therapeutic Area User Guide v1.0. Accessed May 5, 2024. https://www.cdisc.org/standards/therapeutic-areas/diabetes
- Diabetes Type 1 Therapeutic Area User Guide - Screening, Staging and Monitoring of Pre-clinical Type 1 Diabetes. Accessed May 5, 2024. https://www.cdisc.org/standards/therapeutic-areas/diabetes-type-1-screening-staging-and-monitoring-pre-clinical-type-1-0
- Diabetic Kidney Disease Therapeutic Area User Guide v1.0. Accessed May 5, 2024. https://www.cdisc.org/standards/therapeutic-areas/diabetic-kidney-disease/diabetic-kidney-disease-therapeutic-area-user
- Dyslipidemia Therapeutic Area User Guide v1.0. Assessed May 5, 2024. https://www.cdisc.org/standards/therapeutic-areas/dyslipidemia/dyslipidemia-therapeutic-area-user-guide-v1-0
- Polycystic Kidney Disease (PKD) Therapeutic Area User Guide v1.0. Accessed May 5, 2024. https://www.cdisc.org/standards/therapeutic-areas/polycystic-kidney-disease/polycystic-kidney-disease-pkd-therapeutic
- CDISC Examples Collection. Accessed May 5, 2024. https://www.cdisc.org/kb/examples
- CDISC Wiki. Accessed May 5, 2024. https://wiki.cdisc.org/
- CDISC Biomedical Concepts. Accessed May 13, 2024. https://www.cdisc.org/cdisc-biomedical-concepts