Of 1,495 unique citations, 131 articles underwent full-text review of which 30 reviews were deemed eligible for the larger report (Fig. 1) [9,10,11]. Of these, 3 SRs were eligible for this review of reviews (tools that predict risk of DFU or amputation). Two SRs were rated low ROB [9, 11] and one was rated moderate ROB [10]. Detailed characteristics and conclusions of the 3 SRs are provided in Table 1. Across these three SRs, there was heterogeneity in the populations, models, and outcomes of the included studies, and the SRs reached different conclusions. We first provide results from eligible SRs, then describe performance characteristics of the top performing prediction models (distinguishing models used for risk classification versus risk prediction) and finally we reviewed usability characteristics.

Fig. 1

Literature Flow Diagram. *Search through January 13, 2023

Table 1 Overview of systematic reviews evaluating, for patients with diabetes, risk prediction tools for diabetic foot ulcer development or amputationSystematic reviews of prediction tools

The SR by Beulens et al. (low ROB) identified tools that predicted DFU or amputation risk in patients with type 2 diabetes (without a DFU at baseline) with ≥ 1-year follow-up [9]. Beulens et al. identified 21 studies of 34 risk prediction models predicting neuropathy, DFU, or amputation. The commonly used prediction horizons were 1 year and 10 years. The authors also conducted an external validation study of 13 models predicting DFU or amputation using a Dutch cohort of community-dwelling adults with type 2 diabetes mellitus (mean age 67 years, 53% male, 4.1% with a history of DFU or amputation) seen in a primary care clinic (n = 7,624) using a 5-year follow-up period. In this external validation cohort, 485 (6.4%) developed a new DFU and 70 (0.9%) underwent amputation during the 5-year follow-up. Among individuals with no history of DFU or amputation (n = 7309; 95.9% of entire cohort), 265 (3.6%) developed a DFU and 28 (0.4%) underwent amputation over 5 years. In contrast, among individuals with a prior DFU or amputation (n = 315), 220 (69.8%) developed a DFU and 42 (13.3%) underwent amputation over 5 years.

Based on the external validation results, the authors identified top-performing models for:

(i)

Predicting new DFU at 5 years: The Boyko [15], PODUS 2015 [16], and Martins-Mendes (original and simplified) [17] models performed well with good to excellent discrimination. Calibration plots for the Martins-Mendes models (original and simplified) demonstrated good agreement between observed and predicted rates in the lower quintiles of predicted risk, but observed risks exceeded predicted risks in the higher quintiles. No calibration plots were presented for the models by Boyko or PODUS 2015.

(ii)

Predicting amputation at 5 years: The Martins-Mendes models (original and simplified) performed well with good to excellent discrimination (C statistic 0.81 and 0.78, respectively). Calibration plots for these models for amputation showed results similar to their performance for DFU prediction, i.e., good agreement for amputation prediction between observed and predicted risks in the lower quintiles of predicted risk, but observed risks exceeded predicted risks in the higher quintiles of predicted risk.

The authors concluded that using a combined endpoint of DFU or amputation prediction, the models by Boyko, PODUS 2015, and Martins-Mendes showed good performance and may be applicable for use in clinical practice.

The SR by Fernandez-Torres et al. [10] (moderate ROB) identified clinician-assessment tools for measuring diabetic foot disease related variables which included neuropathy and ulceration risk, and DFU-related variables which included amputation risk, healing, infection assessment, and measurement, applicable to patients with diabetes (type 1 or 2). Studies were excluded if tools did not include psychometric properties in their development or did not provide any measurement properties that met the consensus-based standards for the selection of health measurement instruments (COSMIN) criteria. This SR identified 29 studies of 39 clinician-assessment tools validated for the assessment of diabetic foot disease and DFU-related variables. Prediction horizons were not reported. Thus, measures of calibration and discrimination or absolute risks of diabetic foot disease or DFU related outcomes over a specified time horizon were not reported. ROB of included studies was not reported. Of the 10 scales assessing ulceration risk, the authors identified the Queensland High Risk Foot Form scale (QHRFF) as a valid and reliable instrument for assessing risk of developing a DFU. However, the authors also stated that the psychometric characteristics of QHRFF did not have sufficient strength, because the QHRFF validation study was conducted in only 22 subjects.

The SR by Monteiro-Soares et al. [11] (low ROB) identified risk stratification systems for predicting DFU and identified 13 studies evaluating 5 models. The authors stated that the quality of evidence for these systems was low, as little validation of their predictive ability had been performed. Hence, the authors concluded that the best method for assessment of risk stratification was not immediately apparent.

Re-classification and performance characteristics of prediction tools

Based on the results and conclusions of the 3 SRs described above, we identified 5 recommended tools to predict DFU or amputation risk: Boyko et al., Martins-Mendes et al. (simplified and original), PODUS 2015, and QHRFF [9,10,11]. We additionally identified an updated model for PODUS 2015 – PODUS 2020 [8] from a review of the reference lists of SRs. Hence, in total we prioritized 6 tools for further review. For these, we reviewed original studies outlining tool development and ultimately categorized tools as risk classification systems or risk prediction models [8, 15,16,17,18,19,20] described in Appendix Tables 3 and 4. We determined that PODUS 2015 and QHRFF are best categorized as risk classification systems as they do not specify the time horizon for prediction, hence we excluded these from further consideration. We describe below prognostic accuracy of the following risk prediction models: Boyko, Martins-Mendes (original and simplified), and PODUS 2020. All 4 risk prediction models predict DFU; the 2 Martins-Mendes models also predict amputation. The models by Boyko and Martins-Mendes categorize risk subjectively, in contrast to PODUS 2020 which predicts absolute risk.

Prognostic accuracy

All 4 risk prediction models have been externally validated. The Beulens et al. SR externally validated the models by Boyko and Martins-Mendes [9]. PODUS 2020 was externally validated by the study team [8]. Prognostic accuracy (calibration and discrimination) in validation studies for these models is described in Table 2.

Table 2 Performance characteristics of recommended risk prediction models for diabetic foot ulcer development or amputationDiscrimination

In external validation studies, discrimination was good to excellent for all 4 models (Boyko, Martins-Mendes (original and simplified), and PODUS 2020) predicting DFU, and the 2 models (Martins-Mendes) predicting amputation [9].

Calibration

In external validation studies, calibration plots for the models by Martins-Mendes (for DFU and amputation prediction) and PODUS 2020 (for DFU prediction) showed good agreement between observed and predicted absolute risks in the lower quintiles of predicted risk, but observed risk exceeded predicted risk in the higher quintiles [9].

Usability characteristics of prediction tools

Table 3 and Appendix Table 3 describe variables included, score calculation, and score interpretation for the 4 recommended risk prediction models. The 4 models include 2 to 7 variables which can be obtained by history or chart review (prior DFU, prior amputation, and diabetes complications), physical exam (neuropathy, peripheral arterial disease [PAD], fungal infection, and physical impairment), diagnostic testing in the clinic (visual acuity), and laboratory tests (microbiology to assess for onychomycosis or tinea pedis, and HbA1c). The models by Boyko and Martins-Mendes (original or simplified) require a calculator to determine risk score, but PODUS 2020 score is a simple addition (not requiring a calculator). The models by Boyko and Martins-Mendes (original or simplified) provide a subjective assessment of DFU or amputation risk, but PODUS 2020 quantifies absolute average DFU risk at 2 years of follow-up.

Table 3 Variables included in risk prediction models for diabetic foot ulcer development or amputation