Can clinical features be used to differentiate type 1 from type 2 diabetes? A systematic review of the literature
Open accessAbstract
OBJECTIVE: Clinicians predominantly use clinical features to differentiate type 1 from type 2 diabetes yet there are no evidence-based clinical criteria to aid classification of patients. Misclassification of diabetes is widespread (7-15% of cases), resulting in patients receiving inappropriate treatment. We sought to identify which clinical criteria could be used to discriminate type 1 and type 2 diabetes. DESIGN: Systematic review of all diagnostic accuracy studies published since 1979 using clinical criteria to predict insulin deficiency (measured by C-peptide). DATA SOURCES: 14 databases including: MEDLINE, MEDLINE in Process and EMBASE. The search strategy took the form of: (terms for diabetes) AND (terms for C-Peptide). ELIGIBILITY CRITERIA: Diagnostic accuracy studies of any routinely available clinical predictors against a reference standard of insulin deficiency defined by cut-offs of C-peptide concentrations. No restrictions on race, age, language or country of origin. RESULTS: 10,917 abstracts were screened, and 231 full texts reviewed. 11 studies met inclusion criteria, but varied by age, race, year and proportion of participants who were C-peptide negative. Age at diagnosis was the most discriminatory feature in 7/9 studies where it was assessed, with optimal cut-offs (>70% mean sensitivity and specificity) across studies being <30 years or <40 years. Use of/time to insulin treatment and body mass index (BMI) were also discriminatory. When combining features, BMI added little over age at diagnosis and/or time to insulin (<1% improvement in classification). CONCLUSIONS: Despite finding only 11 studies, and considerable heterogeneity between studies, age at diagnosis and time to insulin were consistently the most discriminatory criteria. BMI, despite being widely used in clinical practice, adds little to these two criteria. The criteria identified are similar to the Royal College of General Practitioners National Health Service (RCGP/NHS) Diabetes classification guidelines, which use age at diagnosis <35 years and time to insulin <6 m. Until further studies are carried out, these guidelines represent a suitable classification scheme. SYSTEMATIC REVIEW REGISTRATION: PROSPERO reference CRD42012001736.
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The majority of older adults with low BMI will have type 2 diabetes.
“The majority of older adults with low BMI will have type 2 diabetes (9,12,13), even more so when a person's ethnicity is associated with high type 2 diabetes risk (14).”
From The management of type 1 diabetes in adults. A consensus report by the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD) (2021) · cites this paper as [9]
The Discussion (Principal findings; page unavailable) says age at diagnosis is more useful than BMI for distinguishing diabetes type, and that BMI adds less than 1% to classification based on age. This supports the point that low BMI need not indicate type 1 diabetes, but the paper does not establish that a majority of older adults with low BMI have type 2 diabetes. (LLM, conf=0.78)
Experimental — accuracy not yet measuredThe absence of autoantibodies does not exclude type 1 diabetes.
“The absence of autoantibodies does not exclude type 1 diabetes, since approximately 5-10% of White European people with new-onset type 1 diabetes have negative islet antibodies (8,9,25), and further consideration of the diagnosis is necessary.”
From The management of type 1 diabetes in adults. A consensus report by the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD) (2021) · cites this paper as [9]
The Background (page unavailable) describes islet autoantibodies as imperfect measures for distinguishing type 1 from type 2 diabetes, which supports caution about using them to rule out type 1 diabetes. The paper does not state that an antibody-negative result fails to exclude type 1 diabetes, or give the citing sentence’s 5–10% figure; its Methods say antibody-only studies were excluded. (LLM, conf=0.78)
Experimental — accuracy not yet measuredNo single clinical feature confirms type 1 diabetes in isolation.
“No single clinical feature confirms type 1 diabetes in isolation (9,10).”
Approximately 5-10% of White European people with new-onset type 1 diabetes have negative islet antibodies.
“The absence of autoantibodies does not exclude type 1 diabetes, since approximately 5-10% of White European people with new-onset type 1 diabetes have negative islet antibodies (8,9,25), and further consideration of the diagnosis is necessary.”
From The management of type 1 diabetes in adults. A consensus report by the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD) (2021) · cites this paper as [9]
The Methods (Inclusion and exclusion criteria; page unavailable) say that studies examining islet autoantibodies alone were excluded. The Discussion (Implications and future work; page unavailable) mentions antibodies as a possible diagnostic test but gives no estimate for antibody-negative, newly diagnosed White European patients. Searches for the 5–10% figure and antibody-negative type 1 diabetes found no supporting passage in our copy. (LLM, conf=0.76)
Experimental — accuracy not yet measured
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- Authors
- Shields, B. M., Peters, J. L., Cooper, C., Lowe, J., Knight, B. A., Powell, R. J., Jones, A., Hyde, C. J., & Hattersley, A. T.
- Affiliations
- University of Exeter (GB)
- Royal Devon & Exeter NHS Foundation Trust (GB)
- Corresponding author
- Hattersley, Andrew T
- ORCID
- Venue
- BMJ Open
- Publisher
- BMJ
- Published
- 2015-11
- Volume
- 5
- Issue
- 11
- Pages
- e009088
- ISSN
- 2044-6055 (ISSN-L)
- PMC
- PMC4636628
- OpenAlex
- W1961610877
- Cited by
- 126
- References
- 5
- Citations by year
- 2026: 14 · 2025: 14 · 2024: 8 · 2023: 13 · 2022: 25 · 2021: 7 · 2020: 13 · 2019: 6 · 2018: 11 · 2017: 8 · 2016: 7
- FWCI
- 1.10
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- BMJ Open (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Figshare (submittedVersion)
- Open Research Exeter (University of Exeter) (submittedVersion, cc-by)
- Royal Devon and Exeter Research Repository (Royal Devon and Exeter) (submittedVersion)
- Bristol Research (University of Bristol) (submittedVersion, other-oa)
- Funders
- Royal Devon and Exeter NHS Foundation Trust
- Wellcome Trust (098395)
- National Institute for Health and Care Research (DRF-2010-03-72, CL-2014-23-001, PB-PG-0711-25111, NF-SI-0611-10219)
- Research for Patient Benefit Programme
- NIHR Exeter Clinical Research Facility
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Diabetes and associated disorders
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Treatment and Management
- Keywords
- type 1 diabetes, type 2 diabetes, diabetes classification, C-peptide, insulin deficiency, age at diagnosis, body mass index, clinical criteria, diagnostic accuracy
- MeSH terms
- Diabetes Mellitus, Type 1, Diabetes Mellitus, Type 2, Diagnosis, Differential, Humans
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