Prognostic models for predicting the risk of foot ulcer or amputation in people with type 2 diabetes: a systematic review and external validation study

Beulens, Joline W.J.; Yauw, J. S.; Elders, Petra; Feenstra, Talitha; Herings, Ron M. C.; Slieker, Roderick C.; Moons, Karel G.M.; Nijpels, Giel; Heijden, Amber A. van der

doi:10.1007/s00125-021-05448-w

Cited by 18 publications

(39 citation statements)

References 44 publications

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“…1) (10,12,13). Two SRs were rated low ROB (10,13) and one was rated moderate ROB (12). Detailed characteristics and conclusions of the 3 SRs are provided in Table 1.…”

Section: Resultsmentioning

confidence: 99%

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Risk Prediction Models for Diabetic Foot Ulcer Development or Amputation: A Review of Reviews

Kaka

Landsteiner

Ensrud

et al. 2022

Preprint

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Background In adults with diabetes, diabetic foot ulcer (DFU) and amputation are common and associated with significant morbidity and mortality. Purpose Identify tools predicting risk of DFU or amputation that are prognostically accurate and clinically feasible. Methods We searched for systematic reviews (SRs) of tools predicting DFU or amputation published in multiple databases from initiation to July 2021. We assessed risk of bias (ROB) and provided a narrative review of reviews describing performance characteristics (calibration and discrimination) of prognostically accurate tools. For such tools, we additionally reviewed original studies to ascertain implementation clinical applicability and feasibility (variables included, score calculation, and risk categorization). Results We identified 3 eligible SRs predicting DFU or amputation risk. Two recent SRs (2020 and 2021) were rated as moderate and low ROB respectively. Four risk prediction models – Boyko, Martins-Mendes (simplified), Martins-Mendes (original), and PODUS 2020 had good prognostic accuracy for predicting DFU or amputation over time horizons ranging from 1- to 5-years. PODUS 2020 predicts absolute average risk (e.g., 6% risk of DFU at 2 years) and consists of 3-binary variables with a simple, summative scoring (0–4) making it feasible for clinic implementation. The other 3 models categorize risk subjectively (e.g., high-risk for DFU at 3 years), include 2–7 variables, and require a calculation device. No data exist to inform rescreening intervals. Furthermore, the effectiveness of targeted interventions in decreasing incidence of DFU or amputation in response to prediction scores is unknown. Conclusions In this review of reviews, we identified 4 prognostically accurate models that predict DFU or amputation in persons with diabetes. The PODUS 2020 model, predicting absolute average DFU risk at 2 years, has the most favorable prognostic accuracy and is clinically feasible. Rescreening intervals and effectiveness of intervention based on prediction score are uncertain.

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“…1) (10,12,13). Two SRs were rated low ROB (10,13) and one was rated moderate ROB (12). Detailed characteristics and conclusions of the 3 SRs are provided in Table 1.…”

Section: Resultsmentioning

confidence: 99%

“…All 4 risk prediction models have been externally validated. The Beulens et al SR externally validated the models by Boyko and Martins-Mendes (10). PODUS 2020 was externally validated by the study team (8).…”

Section: Prognostic Accuracymentioning

confidence: 99%

Risk Prediction Models for Diabetic Foot Ulcer Development or Amputation: A Review of Reviews

Kaka

Landsteiner

Ensrud

et al. 2022

Preprint

View full text Add to dashboard Cite

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“…However, most did not allow estimation of absolute risks, thus limiting risk stratification and interpretation to the relative scale and ruling out the assessment of model calibration. The C statistic (95% CI) of 13 models in the DCS study sample [57] for the composite outcome (including foot ulcer and amputation) ranged from 0.53 (0.51, 0.55) to 0.84 (0.82, 0.86), with the model by Boyko et al [58] reaching the highest. One of the few models developed in individuals with type 1 diabetes to predict neuropathy-related outcomes showed good discriminatory ability in the type 1 diabetes subsample of the external validation cohort.…”

Section: Risk Models For the Prediction Of Microvascular Complicationsmentioning

confidence: 98%

“…Neuropathy A recent systematic review summarised available models predicting polyneuropathy and foot ulcer or amputation as hard endpoints of neuropathy in individuals with diabetes and identified 34 prognostic models [57]. However, most did not allow estimation of absolute risks, thus limiting risk stratification and interpretation to the relative scale and ruling out the assessment of model calibration.…”

Section: Risk Models For the Prediction Of Microvascular Complicationsmentioning

confidence: 99%

Precision prognostics for the development of complications in diabetes

Schiborn

Schulze

2022

Diabetologia

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Individuals with diabetes face higher risks for macro- and microvascular complications than their non-diabetic counterparts. The concept of precision medicine in diabetes aims to optimise treatment decisions for individual patients to reduce the risk of major diabetic complications, including cardiovascular outcomes, retinopathy, nephropathy, neuropathy and overall mortality. In this context, prognostic models can be used to estimate an individual’s risk for relevant complications based on individual risk profiles. This review aims to place the concept of prediction modelling into the context of precision prognostics. As opposed to identification of diabetes subsets, the development of prediction models, including the selection of predictors based on their longitudinal association with the outcome of interest and their discriminatory ability, allows estimation of an individual’s absolute risk of complications. As a consequence, such models provide information about potential patient subgroups and their treatment needs. This review provides insight into the methodological issues specifically related to the development and validation of prediction models for diabetes complications. We summarise existing prediction models for macro- and microvascular complications, commonly included predictors, and examples of available validation studies. The review also discusses the potential of non-classical risk markers and omics-based predictors. Finally, it gives insight into the requirements and challenges related to the clinical applications and implementation of developed predictions models to optimise medical decision making. Graphical abstract

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“…Although complications cannot be prevented completely by the currently available therapeutic options, early interventions can delay their onset [11] and prevent potentially severe disease progression. Although several risk scores for diabetic complications exist (reviewed in [12][13][14][15][16][17][18]), they are not used regularly in clinical practice [19] or are recommended by health organizations [2, 19,20]. Therefore, the demand for a risk score with high predictive power that is based on reliable and well-assessable data is still not met.…”

Section: Introductionmentioning

confidence: 99%

DNA Methylation Age Acceleration, Type 2 Diabetes, and its Complications: Cross-sectional and Longitudinal Data from the Berlin Aging Study II (BASE-II)

Vetter

Spieker

Sommerer

et al. 2022

Preprint

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Patients with diabetes mellitus are at risk for micro- and macrovascular complications that are responsible for a substantial part of the individual health burden and socio-economic costs. Therefore, implementable risk scores are needed to improve targeted prevention for patients that are particularly susceptible to complications. The "epigenetic clock" estimates an individual's biological age using DNA methylation profiles and was previously shown to be associated with morbidity and mortality. In this study, we examine older adults of the BASE-II study that were reexamined on average 7.4 years after baseline assessment as part of the GendAge study. For DNA methylation age (DNAmA) estimation we used the 7-CpG clock which was available for two timepoints (n=1,071 at follow-up). In addition, we determined epigenetic age using Horvath's clock, Hannum's clock, PhenoAge and GrimAge which were available at follow-up only (n=1,067). The deviation of DNAmA from chronological age, DNA methylation age acceleration (DNAmAA), was calculated as residuals of a leukocyte cell count adjusted linear regression analysis. Diabetes associated complications were assessed with the Diabetes Complications Severity Index (DCSI). Cross-sectionally, a statistically significant association between oral glucose tolerance test results and Hannum (beta=0.8, SE=0.3, p=0.02, n=762) and PhenoAge DNAmAA (beta=0.8, SE=0.3, p=0.003, n=762) was found. PhenoAge was also associated with fasting glucose (beta=0.3, SE=0.1, p=0.013, n=966). In contrast, we observed no cross-sectional association after covariate adjustment between DNAmAA and a diagnosis of diabetes mellitus with any of the five clocks employed. This was true for longitudinal analyses with the 7-CpG clock as well. However, longitudinal analyses showed that every year in the 7-CpG-based DNAmAA estimate at baseline increased the risk for developing of one or more additional complications or worsening of an already existing complication during the follow-up period by 11% in male participants with diabetes mellitus type 2. This association persisted after adjustment for DCSI at baseline, chronological age, smoking, alcohol, diabetes medication, and BMI (OR =1.11, p=0.045, n=56). No statistically significant association was found in the subgroup of women or when the whole dataset was analyzed (p>0.05). Although our findings still need to be independently validated, the 7-CpG clock appears to be a promising biomarker which is informative about the individual risk for diabetic complications independent of age, sex, lifestyle factors, or complications at baseline.

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Prognostic models for predicting the risk of foot ulcer or amputation in people with type 2 diabetes: a systematic review and external validation study

Cited by 18 publications

References 44 publications

Risk Prediction Models for Diabetic Foot Ulcer Development or Amputation: A Review of Reviews

Risk Prediction Models for Diabetic Foot Ulcer Development or Amputation: A Review of Reviews

Precision prognostics for the development of complications in diabetes

DNA Methylation Age Acceleration, Type 2 Diabetes, and its Complications: Cross-sectional and Longitudinal Data from the Berlin Aging Study II (BASE-II)

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