Clinical usefulness and cost effectiveness of fractional flow reserve among Indian patients (FIND study)

Validity and Diagnostic Performance of Computing Fractional Flow Reserve From 2-Dimensional Coronary Angiography Images

BACKGROUND

Measurement of fractional flow reserve (FFR) is the gold standard for determining the physiologic significance of coronary artery stenosis, but newer software programs can calculate the FFR from 2-dimensional angiography images.

METHODS

A retrospective analysis was conducted using the records of patients with intermediate coronary stenoses who had undergone adenosine FFR (aFFR). To calculate the computed FFR, a software program used simulated coronary blood flow using computational geometry constructed using at least 2 patient-specific angiographic images. Two cardiologists reviewed the angiograms and determined the computational FFR independently. Intraobserver variability was measured using κ analysis and the intraclass correlation coefficient. The correlation coefficient and Bland-Altman plots were used to assess the agreement between the calculated FFR and the aFFR.

RESULTS

A total of 146 patients were included, with 95 men and 51 women, with a mean (SD) age of 61.1 (9.5) y. The mean (SD) aFFR was 0.847 (0.072), and 41 patients (27.0%) had an aFFR of 0.80 or less. There was a strong intraobserver correlation between the computational FFRs (r = 0.808; P < .001; κ = 0.806; P < .001). There was also a strong correlation between aFFR and computational FFR (r = 0.820; P < .001) and good agreement on the Bland-Altman plot. The computational FFR had a high sensitivity (95.1%) and specificity (90.1%) for detecting an aFFR of 0.80 or less.

CONCLUSION

A novel software program provides a feasible method of calculating FFR from coronary angiography images without resorting to pharmacologically induced hyperemia.

Coronary artery disease management and cost implications with fractional flow reserve guided coronary intervention in Indian patients with stable ischemic coronary artery disease

OBJECTIVES

To study the safety of stent avoidance, frequency of change in management decisions, and its cost implications while using a fractional flow reserve (FFR)-guided treatment strategy for intermediate-grade coronary artery stenosis.

BACKGROUND

The impact of FFR in guiding management decisions and its cost implications has not been studied after imposition of a ceiling on stent prices by the Government of India.

METHODS

In 400 patients with 477 intermediate-grade coronary lesions for whom coronary intervention was planned, functional assessment using FFR was done. Incidence of the primary composite endpoint (major adverse cardiac event [MACE], cardiac death, myocardial infarction, objective evidence of ischemia, and target vessel revascularization) in the stent avoided subset was compared with the stented group at follow-up. Micro-costing analysis was done using a computed model with current stent and FFR wire prices.

RESULTS

The overall incidence of MACE was 4.9%, 0.9% in the stent-avoided subset and 6.9% in stented group (p = 0.04, comparing the latter two) at a median follow-up of 21 months (interquartile range 12-31 months). Serious adverse events occurred only in 1% of patients receiving adenosine. The average cost saving was Indian rupees (INR) 51,847 [United States Dollar (USD) 746] per patient, resulting in total savings of INR 15,813,379 (USD 227,530). Cost savings persisted but were lower by 36% (INR 18,613/USD 268 per patient) after the ceiling of stent prices.

CONCLUSION

FFR-guided percutaneous coronary intervention (PCI) strategy is safe and cost-effective in countries where majority of patients self-finance their health care, resulting in stent and PCI avoidance in approximately one in three patients referred for coronary angioplasty.

Cost-effectiveness of interventions to control cardiovascular diseases and diabetes mellitus in South Asia: a systematic review

OBJECTIVES

More than 80% of cardiovascular diseases (CVD) and diabetes mellitus (DM) burden now lies in low and middle-income countries. Hence, there is an urgent need to identify and implement the most cost-effective interventions, particularly in the resource-constraint South Asian settings. Thus, we aimed to systematically review the cost-effectiveness of individual-level, group-level and population-level interventions to control CVD and DM in South Asia.

METHODS

We searched 14 electronic databases up to August 2016. The search strategy consisted of terms related to 'economic evaluation', 'CVD', 'DM' and 'South Asia'. Per protocol two reviewers assessed the eligibility and methodological quality of studies using standard checklists, and extracted incremental cost-effectiveness ratios of interventions.

RESULTS

Of the 2949 identified studies, 42 met full inclusion criteria. Critical appraisal of studies revealed 15 excellent, 18 good and 9 poor quality studies. Most studies were from India (n=37), followed by Bangladesh (n=3), Pakistan (n=2) and Bhutan (n=1). The economic evaluations were based on observational studies (n=9), randomised trials (n=12) and decision models (n=21). Together, these studies evaluated 301 policy or clinical interventions or combination of both. We found a large number of interventions were cost-effective aimed at primordial prevention (tobacco taxation, salt reduction legislation, food labelling and food advertising regulation), and primary and secondary prevention (multidrug therapy for CVD in high-risk group, lifestyle modification and metformin treatment for diabetes prevention, and screening for diabetes complications every 2-5 years). Significant heterogeneity in analytical framework and outcome measures used in these studies restricted meta-analysis and direct ranking of the interventions by their degree of cost-effectiveness.

CONCLUSIONS

The cost-effectiveness evidence for CVD and DM interventions in South Asia is growing, but most evidence is from India and limited to decision modelled outcomes. There is an urgent need for formal health technology assessment and policy evaluations in South Asia using local research data.

PROSPERO REGISTRATION NUMBER

CRD42013006479.