10.1161/CIRCULATIONAHA.122.061754

Efficacy and Safety of Dapagliflozin According to Frailty in Patients with
Heart Failure: A Prespecified Analysis of the DELIVER Trial

Running Title: Butt et al.; Dapagliflozin and frailty in HFmrEF and HFpEF

Jawad H. Butt, MD1,2; Pardeep S. Jhund, MBChB, MSc, PhD1; Jan Belohlávek, MD, PhD3;
Rudolf A. de Boer, MD, PhD4; Chern-En Chiang, MD, PhD5; Akshai S. Desai, MD, MPH6;
Jarosław Drożdż, MD, PhD7; Adrian F. Hernandez, MD8; Silvio E. Inzucchi, MD9; Tzvetana
Katova, MD, PhD10; Masafumi Kitakaze, MD, PhD11; Mikhail N. Kosiborod, MD12; Carolyn
S. P. Lam, MD13; Anna Maria Langkilde, MD, PhD14; Daniel Lindholm, MD, PhD14;
Erasmus Bachus, MD, PhD14; Felipe Martinez, MD15; Béla Merkely, MD, PhD16; Magnus
Petersson, MD, PhD14; Jose F. Kerr Saraiva, MD, PhD17; Sanjiv J. Shah, MD18; Muthiah
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Vaduganathan, MD, MPH19; Orly Vardeny, PharmD MS20; Ulrica Wilderäng, PhD14; Brian
C. Claggett, PhD19; Scott D. Solomon, MD19; John J.V. McMurray, MD1

1

British Heart Foundation Cardiovascular Research Centre, University of Glasgow, Glasgow,
UK; 2Department of Cardiology, Rigshospitalet Copenhagen University Hospital,

Copenhagen, Denmark; 3Second Department of Internal Medicine, Cardiovascular Medicine,
General Teaching Hospital, First Faculty of Medicine, Charles University, Prague, Czech
Republic; 4University of Groningen, Groningen, the Netherlands; 5General Clinical ResearchCenter and Division of Cardiology, Taipei Veterans General Hospital and National Yang
Ming Chiao Tung University, Taipei, Taiwan; 6Division of Cardiovascular Medicine,
Brigham and Women’s Hospital, Boston, MA; 7Department of Cardiology, Medical
University of Lodz, Lodz, Poland; 8Duke University Medical Center, Durham, NC; 9Yale
School of Medicine, New Haven, CT; 10Department of Noninvasive Cardiology, National1

10.1161/CIRCULATIONAHA.122.061754

Cardiology Hospital, Sofia, Bulgaria; 11Cardiovascular Division of Medicine, National
Cerebral and Cardiovascular Center, Osaka, Japan; 12Saint Luke's Mid America Heart
Institute, Kansas City, MO; 13National Heart Centre Singapore & Duke-National Universityof Singapore, Singapore; 14Late-Stage Development, Cardiovascular, Renal, and Metabolism,
BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden; 15University of Cordoba,
Cordoba, Argentina; 16Heart and Vascular Centre, Semmelweis University, Budapest,
Hungary; 17Cardiovascular Division, Instituto de Pesquisa Clínica de Campinas, Campinas
SP, Brazil; 18Northwestern University Feinberg School of Medicine, Chicago, IL;
19

Cardiovascular Division, Brigham and Women's Hospital, Harvard Medical School,

Boston, MA; 20Minneapolis VA Center for Care Delivery and Outcomes Research,
University of Minnesota, Minneapolis, MN
Address for Correspondence:
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Professor John J.V. McMurray
British Heart Foundation Cardiovascular Research Centre
University of Glasgow
126 University Place,
Glasgow, G12 8TA,
United Kingdom
Tel: +44 141 330 3479
Fax: +44 141 330 6955
Email: john.mcmurray@glasgow.ac.uk*This manuscript was sent to Illeana Piña, Guest Editor, for review by expert referees, editorial decision, andfinal disposition.

**This article is published in its accepted form, it has not been copyedited and has not appeared in an issue ofthe journal. Preparation for inclusion in an issue of Circulation involves copyediting, typesetting, proofreading,and author review, which may lead to differences between this accepted version of the manuscript and the final,
published version.
***This work was presented as an abstract at the ESC Congress, August 26-29, 20222

10.1161/CIRCULATIONAHA.122.061754

Abstract

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Background: Frailty is increasing in prevalence and because frail patients are often
perceived to have a less favorable benefit/risk profile, they may be less likely to receive new
pharmacological treatments. We investigated the efficacy and tolerability of dapagliflozin
according to frailty status in patients with heart failure and mildly reduced and preserved
ejection fraction randomized in DELIVER.
Methods: Frailty was measured using the Rockwood cumulative deficit approach. The
primary endpoint was time to a first worsening heart failure event or cardiovascular death.
Results: Of the 6263 patients randomized, a Frailty Index (FI) was calculable in 6258. In
total, 2,354 (37.6%) patients had class 1 frailty (FI <0.210, i.e., not frail), 2,413 (38.6%) werein class 2 (FI 0.211-0.310, i.e., more frail), and 1,491 (23.8%) had class 3 frailty (FI >0.311,
i.e., most frail). Greater frailty was associated with a higher rate of the primary endpoint (per100 person-years): FI class 1, 6.3 (95% CI 5.7-7.1); class 2, 8.3 (7.5-9.1); and class 3, 13.4
(12.1-14.7), P<0.001. The effect of dapagliflozin (as a hazard ratio) on the primary endpointfrom FI class 1 to 3 was: 0.85 (95% CI, 0.68-1.06); 0.89 (0.74-1.08); and 0.74 (0.61-0.91),
respectively (Pinteraction=0.40). Although frailer patients had worse KCCQ scores at baseline,
the improvement with dapagliflozin was greater than in less frail patients: placebo-corrected
improvement in KCCQ-OSS at 4 months FI class 1, 0.3 (95% CI -0.9 to 1.4); class 2, 1.5(0.3-2.7); and class 3, 3.4 (1.7-5.1) [Pinteraction=0.021]. Adverse reactions and treatment
discontinuation, while more frequent in frailer patients, were not more common withdapagliflozin than placebo, irrespective of frailty class.
Conclusions: In DELIVER, frailty was common and associated with worse outcomes. The
benefit of dapagliflozin was consistent across the range of frailty studied. The improvement
in health-related quality of life with dapagliflozin occurred early and was greater in patientswith greater frailty.
Clinical Trial Registration: Clinicaltrials.gov; Unique identifier: NCT03619213.
Key words: Heart failure; frailty; clinical trial; outcomes.

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Abbreviations
AF: Atrial fibrillation
ATMOSPHERE: Aliskiren Trial of Minimizing OutcomeS in Patients With HEart Failure
DELIVER: Dapagliflozin Evaluation to Improve the LIVEs of Patients With PReserved
Ejection Fraction Heart Failure
ECG: Electrocardiogram
eGFR: Estimated glomerular filtration rate
FI: Frailty Index
HF: Heart failure
HFmrEF: Heart failure with mildly reduced ejection fraction
HFpEF: Heart failure with preserved ejection fraction
HR: Hazard ratio
KCCQ-CSS: Kansas City Cardiomyopathy Questionnaire Clinical Summary Score
KCCQ-OSS: Kansas City Cardiomyopathy Questionnaire Overall Summary Score
KCCQ-TSS: Kansas City Cardiomyopathy Questionnaire Total Symptom Score
LVEF: Left ventricular ejection fraction
NYHA: New York Heart Association
NT-proBNP: N-terminal pro-B-type natriuretic peptide
PARADIGM-HF: Prospective Comparison of ARNI with ACEI to Determine Impact on
Global Mortality and Morbidity in Heart Failure
PARAGON-HF: Prospective Comparison of ARNI With ARB Global Outcomes in Heart
Failure With Preserved Ejection Fraction
RR: Rate ratio
TOPCAT: Treatment of Preserved Cardiac Function with an Aldosterone Antagonist
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10.1161/CIRCULATIONAHA.122.061754

Clinical Perspective
What is new?
•

In a prespecified analysis of the DELIVER trial, greater frailty was associated withmore impairment of health status and clinical outcomes in patients with heart failure
and mildly reduced and preserved ejection fraction.

•

The beneficial effects of dapagliflozin, compared with placebo, on clinical outcomes
were consistent regardless of frailty class, but the improvements in symptoms,
physical function, and quality of life were larger in the frailest patients.

•

Adverse events were not more common in individuals randomized to receive
dapagliflozin compared with placebo, irrespective of frailty class.

What are the clinical implications?
•

The benefit/risk balance related to frailty in patients with heart failure and mildlyreduced and preserved ejection fraction was favorable for dapagliflozin.

•

These findings should challenge any clinical reluctance to introduce dapagliflozin inpatients perceived to be frail.

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10.1161/CIRCULATIONAHA.122.061754

Introduction
Frailty, a syndrome characterized by a decline in homeostatic reserves across multiple
physiological systems and increased vulnerability to endogenous and exogenous stressors, isan increasing health burden globally.1–4 The implications of frailty are substantial not only for
public health, but also for individual patients, who are not only at greater risk of outcomessuch as hospital admission and premature death, but also of falls, reduced mobility, impaired
quality of life, institutional placement, social isolation, and loneliness.1–4 Since physiologicalreserves decline with both age and number of comorbidities, frailty is related to, but not thesame as ageing and multimorbidity. Frailty can also occur in younger people and those
without comorbidities, and poor appetite, fatigue, reduced mobility, and declining cognition,
all of which are manifestations of frailty, are not specific to a particular disease.1–4
Although heart failure (HF) and frailty are two distinct conditions, they often coexist, andeach increases the likelihood and complicates the course, of the other. Thus, patients with HF
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are up to six times more likely to be frail than the general population, and thecatabolic/anabolic imbalance in HF may accelerate the development of frailty.5–9 Frail HF
patients also have a substantially higher risk of functional decline, hospital admissions, anddeath, compared to non-frail HF patients.9–15 Recently, there has also been increasing interestin evaluating the effects of new HF treatments in frail patients. There is a common perceptionthat evidence-based therapies are less effective in frail individuals, and there are concerns thatthese patients have more treatment intolerance, experience more adverse drug reactions, anddrug interactions, and thus are more likely to discontinue treatment.9,10,16–18 Given the
anticipation of a less favorable risk-benefit profile in frail patients, clinicians may be morereluctant to initiate new therapies in such individuals.9,10,16–18 However, there is little evidence
to support this assumption, and frail HF patients may even have greater absolute benefits on
worsening HF events and health-related quality of life with certain pharmacological therapies

610.1161/CIRCULATIONAHA.122.061754

and aerobic exercise training.10,11,15,19–23 This is particularly important given the likely role ofhospitalization and worsening of HF in accelerating frailty.
In the Dapagliflozin Evaluation to Improve the LIVEs of Patients With PReserved Ejection
Fraction Heart Failure (DELIVER) trial, dapagliflozin, compared with placebo, reduced therisk of worsening HF events or cardiovascular death, and improved symptoms, in 6,263
patients with HF and mildly reduced and preserved EF.24 In this pre-specified analysis, we
examined the efficacy and safety of dapagliflozin according to frailty status, using the
Rockwood cumulative deficit approach.

Methods
DELIVER was randomized, double-blind, controlled trial in patients with HF and mildlyreduced and preserved left ventricular ejection fraction (LVEF), comparing the efficacy andsafety of dapagliflozin 10 mg once daily compared to matching placebo, in addition to
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standard care. The design, baseline characteristics, and primary results of DELIVER are
published.24–27 The trial protocol was approved by the Ethics Committee at all participating
institutions, and all patients provided written informed consent. The corresponding author
had full access to all the trial data and takes responsibility for its integrity and the data
analysis. Data underlying the findings described in this manuscript may be obtained
following AstraZeneca’s data sharing policy described athttps://astrazenecagrouptrials.pharmacm.com/ST/Submission/Disclosure.
Study patients
Key inclusion criteria were age >40 years, HF diagnosis >6 weeks with at least intermittent
use of diuretic treatment, New York Heart Association (NYHA) functional class II-IV, a
LVEF >40%, evidence of structural heart disease (either left atrial enlargement or left
ventricular hypertrophy), and an N-terminal pro-B-type natriuretic peptide (NT-proBNP)

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concentration ≥300 pg/mL (>600 pg/mL if atrial fibrillation/flutter on the electrocardiogram[ECG] at enrolment). Both ambulatory and hospitalized patients were eligible. Key exclusion
criteria were type 1 diabetes; estimated glomerular filtration rate (eGFR) <25
mL/min/1.73m2; and systolic blood pressure <95 mmHg. A complete list of exclusion criteria
is provided in the design paper.25
Frailty Index
In the present analysis, frailty was assessed using the Rockwood cumulative deficit approach,and this approach has been described in detail previously.10,11,28–30 Standard criteria forconstructing a frailty index (FI) using this approach are the following: at least 30 items are
required; items must be associated with health status; items must cover a range of bodysystems and not be isolated to one system; items must not be part of normal ageing or
saturate too early (e.g., presbyopia), but they should generally increase with age. We createda 30-item FI, and these items were derived from medical history, vital signs, laboratory data,
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and the EuroQoL-5 Domain questionnaire (health-related quality of life measures, including
functional status) [Table S1]. A score was assigned for each non-missing item, and the FI
score was calculated as the sum of these scores divided by the total number of non-missing
items, with higher scores indicating greater frailty. Binary variables (e.g., a history of MI)
were scored 0/1 (absent/present); ordinal variables (e.g., quality of life measures) were scoredfrom 0 to 1 (in increments of 0.25, with a score of 1 indicating the greatest severity); andcontinuous variables (e.g., creatinine) were categorized and scored as 0/1 (normal/abnormal).
Patients were excluded if they had >20% missing items.10,11,31–33 Patients were divided into
the following three subgroups: FI ≤0.210 (FI class 1) [classified as non-frail patients, as
defined previously]; FI 0.211- 0.310 (FI class 2, i.e., more frail), and FI >0.311 (FI class 3,
i.e., most frail).

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Trial outcomes
The primary outcome in DELIVER was the composite of worsening HF (HF hospitalization
or urgent HF visit) or cardiovascular death. The secondary outcomes in the trial were total HF
events (first and repeat HF hospitalization or an urgent visit for worsening HF) andcardiovascular death; change from baseline to 8 months in the Kansas City Cardiomyopathy
Questionnaire (KCCQ) total symptom score (KCCQ-TSS); cardiovascular death; and allcause mortality. In the present analysis, we also examined the change from baseline to 8
months in the KCCQ overall and clinical summary score (KCCQ-OSS and -CSS,
respectively) and the change in KCCQ-scores from baseline to 4 months; worsening HF, HF
hospitalization and any hospitalization.
Prespecified safety analyses included serious adverse events, adverse events leading todiscontinuation of trial treatment, and selected adverse events, including volume depletion,
renal adverse events, amputation, major hypoglycemia, and diabetic ketoacidosis, for
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consistency across reporting in trials.
Statistical analyses
Baseline characteristics were summarized as frequencies with percentages, means withstandard deviation, or medians with interquartile ranges. Differences in baselinecharacteristics were tested using the Cochran-Armitage trend test for binary variables, theCochran-Mantel-Haenszel test for categorical variables, and the JonckheereTerpstra test andanalysis of variance test for non-normal and normally distributed continuous variables,
respectively.
Regardless of treatment allocation, time-to-event data were evaluated using the Kaplan-Meierestimator (all-cause death), the Aalen-Johansen estimator (all outcomes except all-cause
death), and Cox proportional-hazards models, stratified according to diabetes mellitus status,
and adjusted for treatment assignment, and hazard ratios (HR) with 95% CIs were reported

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for FI (with FI class I as the reference). Total (first and recurrent) events were evaluated withsemiparametric proportional-rates models,34 stratified according to diabetes mellitus status
and adjusted for treatment assignment, and rate ratios (RR) with 95% CIs were reported. In
addition, HRs and RRs, stratified according to diabetes mellitus status, and adjusted fortreatment assignment, age, sex, geographical region, a history of HF hospitalization, HF
duration, log of NT-proBNP, LVEF, and NYHA functional class were reported; variables
which were part of the FI were not adjusted for, since the categorization of FI into the threeclasses were conditioned on these variables.
To compare the effects of dapagliflozin with placebo, time-to-event data and total (first andrecurrent) events were evaluated with Cox proportional-hazards models and semiparametricproportional-rates models, respectively, and these models were stratified according todiabetes mellitus status. HRs and RRs with 95% CI within each FI class were reported. The
effect of dapagliflozin was also examined according to continuous FI as a fractional
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polynomial. The difference between treatment groups in the change in KCCQ-TSS, -CSS,
and -OSS from baseline to 8 months was analyzed using mixed-effect models for repeatedmeasurements, adjusted for baseline value, visit (month 1, 4 and 8), treatment assignment,
and interaction of treatment and visit. The least-squares mean differences with 95% CI
between treatment groups within each FI class were reported. The interaction term between
treatment assignment and visit was included to examine the effect of dapagliflozin, comparedwith placebo, on the mean change in KCCQ scores at 4 and 8 months. To test for interaction
between the treatment effect of dapagliflozin and FI, the Wald test was used for the Cox
proportional-hazards models, the semiparametric proportional-rates models, and the mixedeffect models for repeated measurements.
All analyses were conducted using SAS version 9.4 (SAS Institute, Cary, NC) and STATA
version 17.0 (College Station, TX).

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Results
Patient characteristics
Of the 6,263 patients randomized in DELIVER, FI was calculable for 6,258 patients. The
numbers of patients with missing data for individual components of the FI are shown in
Tables S2 and S3. The distribution of FI is shown in Figure S1. Mean FI was 0.248(standard deviation, 0.092) and median FI was 0.242 (interquartile range, 0.183-0.308; range
0-0.633). In total, 2,354 (37.6%) patients had class 1 frailty (FI <0.210, i.e., not frail), 2,413(38.6%) were in class 2 (FI 0.211-0.310, i.e., more frail), and 1,491 (23.8%) had class 3
frailty (FI >0.311, i.e., most frail).
Baseline characteristics according to FI class are presented in Table 1. Compared to patientswith lower FI, those with higher FI (worse frailty) were older, more often White (and lessoften Asian), more likely to have cardiovascular and non-cardiovascular comorbidities, andDownloaded from http://ahajournals.org by on August 29, 2022

more often smokers. They also had higher systolic blood pressure, BMI, NT-proBNP(irrespective of AF on ECG), and hemoglobin A1c, but lower eGFR. Patients with higher FI
were more likely to have a longer duration of HF, lower LVEF, and worse NYHA functionalclass and KCCQ scores than those with lower FI (i.e., less frailty).
Outcomes according to Frailty Index
Compared to patients in FI class 1 (the least frail), those in FI class 3 (the frailest) had ahigher risk of worsening HF or cardiovascular death; worsening HF; HF hospitalization; any
hospitalization; cardiovascular death; all-cause death; and total HF events and cardiovasculardeath, even after adjustment for known prognostic variables (Figure 1, Table 2). Compared
to individuals in FI class 1, those in FI class 2 also had a higher risk of these outcomes,
although the association between FI class 2 and these outcomes were not statisticallysignificant (except for any hospitalization), after adjustment for prognostic variables.

1110.1161/CIRCULATIONAHA.122.061754

Effects of dapagliflozin on clinical outcomes according to Frailty Index
Primary composite outcome
Compared with placebo, dapagliflozin reduced the risk of worsening HF or cardiovasculardeath across FI classes – the HRs from lowest to highest FI class were: 0.85 [95% CI, 0.681.06], 0.89 [95% CI, 0.74-1.08], and 0.74 [95% CI, 0.61-0.91], respectively. There was nointeraction between FI class (as an ordinal variable) and the effect of dapagliflozin on the
primary outcome (P for interaction=0.40) [Table 2]. The effect of dapagliflozin was also
consistent across the spectrum of continuous FI (P for interaction=0.27) [Figure 2].
In the overall trial, the HR for the primary composite endpoint with dapagliflozin comparedto placebo was 0.82 (95% CI, 0.73-0.92); applying a relative risk reduction of 18% to theplacebo event rate to each FI class resulted in a number of patients needed to treat (NNT) of
40, 31, and 19, respectively, to prevent one primary event over the median follow-up of 2.3
years.
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Secondary outcomes
The effect of dapagliflozin was consistent across FI classes for worsening HF; HF
hospitalization; cardiovascular death; all-cause death; and the composite of total HF events or
cardiovascular death (P for interaction for all outcomes >0.25) [Table 2, Figure 3]. The
effect of dapagliflozin on these outcomes was also consistent across the spectrum ofcontinuous FI (P for interaction >0.11) [Figure 2].
In the overall trial, the HR for HF hospitalization with dapagliflozin compared to placebo was
0.77 (95% CI 0.67-0.89); applying a relative risk reduction of 23% to the placebo event ratein each FI class resulted in NNTs of 48, 37, and 20, in FI classes 1 to 3, respectively, toprevent at least one hospital admission for worsening heart failure over the median follow-up
of 2.3 years.

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Symptoms and health status measured using the KCCQ
At baseline, 5,793 patients (92.6%) had available KCCQ data. At 8 months, 4,485 patients(71.7% of the study population; 74.3% of the study population alive) had available KCCQ
data and 1,773 did not (220 due to death, 1,553 due to other reasons than death). The effect of
dapagliflozin on the mean change in KCCQ-scores was modified by FI class; larger increases(improvements) were seen with dapagliflozin, compared to placebo, at 4 and 8 months among
patients with a higher FI i.e., greater frailty [Table 3].
Safety analyses
The proportions of patients who discontinued trial treatment or experienced adverse events
increased with increasing frailty. However, there were no differences between treatments(dapagliflozin versus placebo) across all FI classes (Table 4).

Discussion
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In this pre-specified analysis of DELIVER, approximately 63% of patients were categorized
as frail. Greater frailty was associated with more impairment in health status and worse
clinical outcomes, including hospitalizations and death. The beneficial effects ofdapagliflozin, compared with placebo, on clinical outcomes were consistent regardless offrailty class. Importantly, the improvements in symptoms, physical function, and quality oflife were larger in the frailest patients. Adverse events, although more frequent in frailer
patients, were not more common in those randomized to dapagliflozin compared withplacebo.
Prevalence of and outcomes according to frailty
The mean FI in DELIVER, calculated using the Rockwood cumulative deficits approach, was
0.248 (standard deviation, 0.092). Generally, a FI ≤0.210 is considered non-frail. In people>65 years participating in the UK Biobank, the mean FI was 0.129.35 Other population

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studies have reported a mean FI ranging from 0.14 to 0.16.36,37 In a trial comparing aspirinwith placebo in 19,114 people aged ≥70 living in the United States (≥65 years in U.S.
minorities) and Australia, and free of cardiovascular disease, persistent physical disability,and dementia, the mean FI was 0.11 and only 8.1% of participants were frail.38 Even inpatients >80 years enrolled in two hypertension trials, the median FI was only 0.17 to
0.18.39,40
Clearly, the higher FI among participants in DELIVER, contrasts strikingly with these earlier
reports, confirming that frailty is much more prevalent in patients with HFmrEF and HFpEF
than in the people participating in the studies mentioned above. The mean FI in DELIVER(0.248) was lower than in patients with HFpEF in TOPCAT-Americas (mean FI 0.37) but
similar to that in the much larger and more global (and therefore more comparable)
PARAGON-HF trial (mean FI 0.227) which also enrolled patients with HFpEF.11
Interestingly, using the same approach, the FI in the generally younger patients with HFrEF
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in the PARADIGM-HF and ATMOSPHERE (mean FI 0.250) and DAPA-HF (0.216) was
similar to that in DELIVER and PARAGON-HF, confirming that frailty is common in all HF
phenotypes and not confined to the very elderly.10,15
Impact of frailty
Increasing frailty was accompanied by a large difference KCCQ scores at baseline (thesewere16 to 17 points lower in the most compared to least frail patients), showing that greater
frailty was associated with much more impairment of health-related quality of life andsymptoms. The magnitude of the difference in KCCQ scores between more and less frail
patients was similar to that observed in both PARAGON-HF and DAPA-HF.15
Increasing frailty was also associated with worse outcomes during follow-up. In DELIVER,
as in PARAGON-HF and the three large HFrEF trials described above, there was a graded
relationship between FI and the standard outcomes reported i.e., the rates of hospitalization

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for HF and cardiovascular death increased with increasing FI.10,15 However, the gradients inthe association between frailty and the broader outcomes of hospital admission for any cause
and death from any cause were, if anything, steeper than for the more specific heart failure
outcomes, emphasizing the more general impact of frailty on health.
Treatment effect of dapagliflozin according to frailty
As alluded to in the introduction, the benefit-risk profile of pharmacological therapy is often
considered less favorable in frail patients, with underutilization and discontinuation ofrecommended treatments in such individuals.9,10,16–18 While it was true that greater frailty was
associated with higher rates of adverse events and discontinuation of randomized treatment,
neither was more common in the dapagliflozin group than in the placebo group. More
importantly, the efficacy of dapagliflozin was not diminished in the frailest patients. We
found there was no statistically significant interaction between frailty and the effects ofdapagliflozin, compared with placebo, for any of the outcomes assessed in our categorical
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analysis and this was confirmed when FI was analysed as a continuous variable. Indeed, there
was a trend towards a greater effect on worsening heart failure events in frailer patients,
consistent with what was observed with sacubitril/valsartan in PARAGON-HF. Because of
the considerably higher event rate in the frailest patients, the absolute benefit was twice aslarge in these individuals as in non-frail participants, emphasizing the importance ofcounteracting any tendency to therapeutic nihilism in patients deemed to be frail.
These findings in DELIVER were consistent with those using dapagliflozin in DAPA-HF
and with sacubitril-valsartan in patients with both HFrEF and HFpEF.15 Although the major
effect in patients with HFpEF was on HF hospitalization, this is of potentially great
importance given the likely role of hospital admission in accelerating frailty, the prevention
and treatment of which has become a key priority in clinical medicine.9,41

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Improvement of health status is another major goal of treatment in patients with HF and thisis all the more so in frailer patients, who have a much greater symptom burden and worse
health-related quality of life than non-frail patients. Interestingly, the improvement insymptom burden and quality of life with dapagliflozin was significantly larger in patientswith greater frailty. This benefit was apparent as early as 4 months after starting treatment.
Symptom control and continuation of daily activities are important, per se, for patients with
HF and may help prevent the development of frailty and progression of existing frailty inthese most vulnerable individuals.
Limitations
The specific inclusion and exclusion criteria in DELIVER precluded the enrolment of themost frail patients, and it is likely that the participants in DELIVER were less frail thanpatients with HFmrEF and HFpEF in the general population. Although the effects ofdapagliflozin on clinical outcomes were consistent across the range of FI in DELIVER (0Downloaded from http://ahajournals.org by on August 29, 2022

0.633), our results may not be generalizable to all patients with HF, and it is possible that thebeneficial effects of this therapy may be attenuated in very frail patients. We were not able totest other frailty scores that include assessments of muscle strength and functional capacity asthese measurements were not made in DELIVER. Finally, given the observational nature of
the analyses on the association between FI and clinical outcomes, the possibility of residual
confounding cannot be fully excluded despite adjustment for measured, known confounders
in our analyses.

Conclusions
In DELIVER, greater frailty was associated with more impairment of health status and worse
clinical outcomes. The relative risk reduction in clinical events with dapagliflozin wasconsistent across frailty classes. The improvement in health-related quality of life with16

10.1161/CIRCULATIONAHA.122.061754

dapagliflozin occurred early and was greater in patients with greater frailty. Adverse eventswere not more common in individuals randomized to dapagliflozin compared with placebo,
irrespective of frailty class. Therefore, the benefit/risk balance related to frailty was favorable
for dapagliflozin. These findings should challenge any clinical reluctance to introduce thisnew therapy in patients perceived to be frail.

Acknowledgements
None

Sources of Funding
The DELIVER trial was funded by AstraZeneca. Profs McMurray and Jhund are supported
by a British Heart Foundation Centre of Research Excellence Grant RE/18/6/34217.

Downloaded from http://ahajournals.org by on August 29, 2022

Disclosures
Dr Butt reports advisory board honoraria from Bayer.
Dr Jhund's employer the University of Glasgow has been remunerated by Astrazeneca forworking on the DAPA-HF and DELIVER trials, personal fees from Novartis andCytokinetics, and grants from Boehringer Ingelheim.
Dr De Boer’s institution, the UMCG, has received research grants and fees (outside thesubmitted work) from AstraZeneca, Abbott, Boehringer Ingelheim, Cardio Pharmaceuticals
Gmbh, Ionis Pharmaceuticals, Inc, Novo Nordisk, and Roche. Dr de Boer has received
speaker fees from Abbott, AstraZeneca, Bayer, Novartis, and Roche (outside the submittedwork).
Dr Chiang has received honoraria and consultation fees from AstraZeneca, Boehringer
Ingelheim, Daiichi-Sankyo, Eli Lilly, Merck Sharp & Dohme, Novartis, Pfizer, and Sanofi.

17

10.1161/CIRCULATIONAHA.122.061754

Dr Desai has received grants and personal fees from AstraZeneca during the conduct of thestudy; personal fees from Abbott, Biofourmis, Boston Scientific, Boehringer Ingelheim,
Corvidia, DalCor Pharma, Relypsa, Regeneron, and Merck; grants and personal fees from
Alnylam and Novartis; and personal fees from Amgen, outside the submitted work.
Dr Drozdz has received personal and institutional research support for DELIVER from
AstraZeneca.
Dr Hernandez has received research support from American Regent, AstraZeneca,
Boehringer Ingelheim, Merck, Novartis, and Verily; and has served as a consultant or on theAdvisory Board for Amgen, AstraZeneca, Bayer, Boehringer Ingelheim, Boston Scientific,
Bristol Myers Squibb, Cytokinetics, Myokardia, Merck, Novartis, and Vifor.
Dr Inzucchi has served on clinical trial committees or as a consultant to AstraZeneca,
Boehringer Ingelheim, Novo Nordisk, Lexicon, Merck, Pfizer, vTv Therapeutics, Abbott, andEsperion; and has given lectures sponsored by Astra-Zeneca and Boehringer Ingelheim.
Downloaded from http://ahajournals.org by on August 29, 2022

Dr Katova has received fees for serving as national coordinator from Novartis andAstraZeneca.
Dr Kitakaze has received grants or contracts from the Japanese government through the Japan
Agency for Medical Research and Development Japan Heart Foundation and has received
payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing or
educational events from AstraZeneca, Ono, Novartis, Tanabe-Mitsubishi, Japan Medical Data
Center, Takeda, Pfizer, Daiichi-Sankyo, Otsuka, Sanofi, Boehringer Ingelheim, Amgen,
Kowa, Toyama-Kagaku, Kureha, Viatris, and Mochida.
Dr Kosiborod has received research grant support from AstraZeneca, and Boehringer
Ingelheim; has served as a consultant or on an advisory board for Amgen, Applied
Therapeutics, AstraZeneca, Bayer, Boehringer Ingelheim, Eli Lilly, Esperion Therapeutics,
Janssen, Merck (Diabetes and Cardiovascular), Novo Nordisk, Sanofi, and Vifor Pharma; has

18

10.1161/CIRCULATIONAHA.122.061754

received other research support from AstraZeneca; and has received honorarium from
AstraZeneca, Boehringer Ingelheim, and Novo Nordisk.
Dr Lam is supported by a Clinician Scientist Award from the National Medical ResearchCouncil of Singapore; has received research support from AstraZeneca, Bayer, Boston
Scientific, and Roche Diagnostics; has served as a consultant or on the advisoryboard/steering committee/executive committee for Actelion, Amgen, Applied Therapeutics,
AstraZeneca, Bayer, Boehringer Ingelheim, Boston Scientific, Cytokinetics, Darma Inc,
Us2.ai, Janssen Research & Development LLC, Medscape, Merck, Novartis, Novo Nordisk,
Radcliffe Group Ltd, Roche Diagnostics, Sanofi, and WebMD Global LLC; and serves as the
cofounder and non-executive director of Us2.ai.
Dr Langkilde is an employee and shareholder of AstraZeneca.
Dr Lindholm is an employee and shareholder of AstraZeneca.
Dr Martinez has received personal fees from AstraZeneca.
Downloaded from http://ahajournals.org by on August 29, 2022

Dr Merkely has received personal fees from AstraZeneca and Servier.
Dr Petersson is an employee and shareholder of AstraZeneca.
Dr Kerr Saraiva has received research grant support from Pfizer, Daichii Sankyo, Sanofi,
Boehringer Ingelheim, Novo Nordisk, AstraZeneca, Janssen, Amgen, and Novartis; and hasreceived honorarium from Boehringer Ingelheim, Novo Nordisk, Astra Zeneca, and Amgen.
Dr Shah has received either personal or institutional research support for DELIVER from
AstraZeneca.
Dr Vaduganathan has received research grant support or served on advisory boards for
American Regent, Amgen, AstraZeneca, Bayer AG, Baxter Healthcare, Boehringer
Ingelheim, Cytokinetics, Lexicon Pharmaceuticals, and Relypsa; speaker engagements with
Novartis and Roche Diagnostics; and participates on clinical endpoint committees for studies
sponsored by Galmed and Novartis.

19

10.1161/CIRCULATIONAHA.122.061754

Dr Vardeny have received either personal or institutional research support for DELIVER
from AstraZeneca.
Dr Wilderäng is an employee and shareholder of AstraZeneca.
Dr Claggett has received consulting fees from Boehringer Ingelheim.
Dr Solomon has received research grants from Actelion, Alnylam, Amgen, AstraZeneca,
Bellerophon, Bayer, Bristol Myers Squibb, Celladon, Cytokinetics, Eidos, Gilead,
GlaxoSmithKline, Ionis, Lilly, Mesoblast, MyoKardia, National Institutes of Health/NHLBI,
Neurotronik, Novartis, NovoNordisk, Respicardia, Sanofi Pasteur, Theracos, US2.AI; and has
consulted for Abbott, Action, Akros, Alnylam, Amgen, Arena, AstraZeneca, Bayer,
Boehringer Ingelheim, Bristol Myers Squibb, Cardior, Cardurion, Corvia, Cytokinetics,
Daiichi-Sankyo, GlaxoSmithKline, Lilly, Merck, Myokardia, Novartis, Roche, Theracos,
Quantum Genomics, Cardurion, Janssen, Cardiac Dimensions, Tenaya, Sanofi-Pasteur,
Dinaqor, Tremeau, CellPro-Thera, Moderna, American Regent, and Sarepta.
Downloaded from http://ahajournals.org by on August 29, 2022

Dr McMurray has received payments through Glasgow University from work on clinical
trials, consulting and other activities from Alnylam, Amgen, AstraZeneca, Bayer, Boehringer
Ingelheim, BMS, Cardurion, Cytokinetics, Dal-Cor, GSK, Ionis, KBP Biosciences, Novartis,
Pfizer, Theracos Personal lecture fees: the Corpus, Abbott, Hikma, Sun Pharmaceuticals,
Medscape/Heart.Org, Radcliffe Cardiology, Servier Director, Global Clinical Trial Partners(GCTP).

Supplemental Materials
Tables S1 – S3
Figure S1

20

10.1161/CIRCULATIONAHA.122.061754

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Table 1. Baseline Characteristics According to Frailty Index

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Age (years), mean (SD)Age (years), N (%)
<=65
66-75
=>76
Sex, N (%)
Women
Men
Race, N (%)
White
Black or African American
Asian
Other
Geographic region, N (%)
Europe and Saudi Arabia
Asia
Latin America
North America
Physiological measures
Systolic blood pressure (mmHg), mean (SD)Diastolic blood pressure (mmHg), mean (SD)Heart rate (bpm), mean (SD)
Body mass index, mean (SD)
Atrial fibrillation/flutter on baseline ECG, N (%)
NT-proBNP (pg/mL), median (IQR)
No atrial fibrillation/flutter on baseline ECG
Atrial fibrillation/flutter on baseline ECG
Hemoglobin A1c (%), mean (SD)Creatinine (μmol/L), mean (SD)eGFR (mL/min/1.73m2), mean (SD)FI <=0.210(not frail)
N=2,35470.1±10.3

FI 0.211-0.310(more frail)
N=2,41372.6±9.0

FI =>0.311(most frail)
N=1,49172.7±8.8726 (30.8)
843 (35.8)
785 (33.3)

486 (20.1)
961 (39.8)
966 (40.0)

290 (19.5)
608 (40.8)
593 (39.8)

1,046 (44.4)
1,308 (55.6)

1,050 (43.5)
1,363 (56.5)

650 (43.6)
841 (56.4)

1,416 (60.2)
50 (2.1)
673 (28.6)
215 (9.1)

1,818 (75.3)
54 (2.2)
401 (16.6)
140 (5.8)

1,201 (80.5)
55 (3.7)
199 (13.3)
36 (2.4)

900 (38.2)
660 (28.0)
594 (25.2)
200 (8.5)

1,298 (53.8)
381 (15.8)
441 (18.3)
293 (12.1)

803 (53.9)
184 (12.3)
146 (9.8)358 (24.0)

123.5±14.0
73.8±9.8
71.9±11.8
28.1±5.8
986 (41.9)
961 (608-1627)
699 (452-1201)
1314 (933-2033)
6.2±1.2
91.1±24.2
68.7±18.0

129.4±14.9
74.0±10.3
71.2±11.530.2±5.9
1,039 (43.1)
1034 (624-1795)
706 (473-1302)
1408 (975-2292)
6.6±1.3
104.4±30.4
59.1±18.3

133.8±15.9
74.1±11.3
71.3±12.0
32.1±6.2
619 (41.5)
1084 (642-1897)
761 (481-1391)
1510 (1019-2484)
7.1±1.6
117.3±34.8
52.1±17.4

25

P-value<0.001<0.0010.79<0.001<0.001<0.0010.34
0.10<0.0010.93<0.001
0.004<0.001<0.001<0.001<0.001

10.1161/CIRCULATIONAHA.122.061754

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eGFR (mL/min/1.73m2), N (%)<60=>60
Smoking status, N (%)
Current
FormerNever
Duration of HF, N (%)
0 - 3 months>3 - 6 months>6 - 12 months>1 - 2 years>2 - 5 years>5 years
Left ventricular ejection fraction (%), mean (SD)
Left ventricular ejection fraction (%), N (%)
<=49
50-59
=>60
NYHA class, N (%)
I
II
III
IV
KCCQ total symptom score, mean (SD)KCCQ clinical summary score, mean (SD)KCCQ overall summary score, mean (SD)
Medical history, N (%)
Hospitalization for HF
Atrial fibrillation/flutter
StrokeStroke/TIA
AnginaMyocardial infarction

697 (29.6)
1,657 (70.4)

1,300 (53.9)
1,112 (46.1)

1,070 (71.8)
421 (28.2)

172 (7.3)
764 (32.5)
1,418 (60.2)

179 (7.4)
887 (36.8)
1,347 (55.8)

133 (8.9)
609 (40.8)
749 (50.2)

263 (11.2)
240 (10.2)
366 (15.6)
397 (16.9)
549 (23.4)
534 (22.7)
54.2±9.1

225 (9.3)
241 (10.0)
328 (13.6)
368 (15.3)
621 (25.7)
630 (26.1)
54.2±8.880 (5.4)
111 (7.4)
146 (9.8)230 (15.4)
398 (26.7)
526 (35.3)
54.1±8.3

818 (34.7)
794 (33.7)
742 (31.5)

816 (33.8)
865 (35.8)
732 (30.3)

481 (32.3)
595 (39.9)
415 (27.8)

1 (0.0)1,943 (82.5)
403 (17.1)
7 (0.3)76.8±19.775.3±18.573.2±18.1

0 (0.0)1,810 (75.0)597 (24.7)
6 (0.2)69.7±21.7
67.9±20.0
66.3±19.6

0 (0.0)956 (64.1)
530 (35.5)
5 (0.3)59.7±22.7
57.9±20.6
56.6±20.2

821 (34.9)
1,188 (50.5)
92 (3.9)
115 (4.9)
227 (9.6)
319 (13.6)

966 (40.0)
1,388 (57.5)
225 (9.3)
294 (12.2)
590 (24.5)
675 (28.0)

750 (50.3)
976 (65.5)280 (18.8)
363 (24.3)
678 (45.5)
643 (43.1)

26<0.001<0.001<0.001

0.67
0.004<0.001<0.001<0.001<0.001<0.001<0.001<0.001<0.001<0.001<0.001

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PCI or CABG
Any coronary artery disease
Any atherosclerotic disease
Peripheral artery diseaseNon-coronary revascularization
Valvular heart disease
Pulmonary embolism
Hypertension
Type 2 diabetes mellitus
Chronic obstructive pulmonary disease
Gout
Malignancy
SyncopeSleep apnea
Neuropathy
Dyslipidemia
Osteoporosis
Treatment, N (%)
Loop diuretic
Other diuretic (excluding loop and MRA)
ACEi
ARB
ACEI/ARB
ARNI
Beta-blocker
MRA
Digoxin
Lipid-lowering medication
Antiplatelet
Anticoagulant
Pacemaker
CRT-P/CRT-D
ICD
ICD/CRT-D

354 (15.0)
694 (29.5)
812 (34.5)
44 (1.9)
7 (0.3)456 (19.4)
16 (0.7)
1,814 (77.1)
558 (23.7)
111 (4.7)
89 (3.8)
58 (2.5)
36 (1.5)
57 (2.4)
33 (1.4)
969 (41.2)
58 (2.5)

869 (36.0)
1,322 (54.8)
1,488 (61.7)
171 (7.1)
52 (2.2)
674 (27.9)
35 (1.5)
2,275 (94.3)
1,165 (48.3)
270 (11.2)
253 (10.5)
106 (4.4)
89 (3.7)
167 (6.9)
185 (7.7)
1,725 (71.5)
139 (5.8)

841 (56.4)
1,146 (76.9)
1,250 (83.8)
278 (18.6)
81 (5.4)535 (35.9)
55 (3.7)
1,459 (97.9)
1,081 (72.5)
310 (20.8)
287 (19.2)
140 (9.4)
135 (9.1)
261 (17.5)
402 (27.0)
1,294 (86.8)
127 (8.5)<0.001<0.001<0.001<0.001<0.001<0.001<0.001<0.001<0.001<0.001<0.001<0.001<0.001<0.001<0.001<0.001<0.001

1,696 (72.1)
489 (20.8)
800 (34.0)
824 (35.0)
1,621 (68.9)
159 (6.8)
1,906 (81.0)
1,134 (48.2)
144 (6.1)
1,179 (50.1)
806 (34.3)
1,160 (49.3)
151 (6.4)
14 (0.6)
34 (1.4)
43 (1.8)

1,836 (76.1)
559 (23.2)
929 (38.5)
897 (37.2)
1,811 (75.1)
94 (3.9)
2,014 (83.5)
976 (40.4)
100 (4.1)
1,750 (72.5)
1,064 (44.1)
1,338 (55.4)
245 (10.2)
42 (1.7)
48 (2.0)72 (3.0)

1,274 (85.4)
295 (19.8)
564 (37.8)550 (36.9)
1,108 (74.3)
48 (3.2)
1,253 (84.0)555 (37.2)
52 (3.5)
1,226 (82.2)
758 (50.8)883 (59.2)
265 (17.8)
44 (3.0)31 (2.1)
53 (3.6)<0.001
0.71
0.007
0.19
<0.001<0.0010.01<0.001<0.001<0.001<0.001<0.001<0.001<0.001
0.12<0.00127

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ACEI, angiotensin-converting enzyme inhibitor; ARB, angiotensin receptor blocker; ARNI, angiotensin receptor-neprilysin inhibitor; BMI, body mass index;
CABG, coronary artery bypass graft surgery; CSS, clinical summary score; CRT, cardiac resynchronization therapy; ECG, electrocardiogram; eGFR,
estimated glomerular filtration rate; FI, frailty index; HF, heart failure; ICD, implantable cardioverter-defibrillator; KCCQ, Kansas City Cardiomyopathy
Questionnaire; LVEF, left ventricular ejection fraction; MRA, mineralocorticoid-receptor antagonist; NYHA, New York Heart Association; NT-proBNP, Nterminal pro-B-type natriuretic peptide; OSS, overall summary score; PCI, percutaneous coronary intervention; SD, standard deviation; TIA, transientischemic attack; TSS, total symptom score.

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Table 2. Outcomes According to Frailty Index

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Primary composite outcome
No. of events (%)
Event rate per 100 person-years (95% CI)
HR (95% CI)*HR (95% CI)**
Worsening HF
No. of events (%)
Event rate per 100 person-years (95% CI)
HR (95% CI)*HR (95% CI)**
HF hospitalization
No. of events (%)
Event rate per 100 person-years (95% CI)
HR (95% CI)*HR (95% CI)**Any hospitalization
No. of events (%)
Event rate per 100 person-years (95% CI)
HR (95% CI)*HR (95% CI)**
Cardiovascular deathNo. of events (%)
Event rate per 100 person-years (95% CI)
HR (95% CI)*HR (95% CI)**
All-cause deathNo. of events (%)
Event rate per 100 person-years (95% CI)
HR (95% CI)*HR (95% CI)**FI <0.210(not frail)
N=2,354

FI 0.211-0.310(more frail)
N=2,413

FI >0.311(most frail)
N=1,491309 (13.1)
6.3 (5.7-7.1)
Reference
Reference

418 (17.3)
8.3 (7.5-9.1)
1.28 (1.10-1.48)
1.13 (0.97-1.32)

394 (26.4)
13.4 (12.1-14.7)
2.00 (1.70-2.34)
1.53 (1.29-1.81)

220 (9.3)
4.5 (3.9-5.1)
Reference
Reference

295 (12.2)
5.9 (5.2-6.6)
1.27 (1.07-1.52)
1.13 (0.94-1.36)

307 (20.6)
10.4 (9.3-11.6)
2.20 (1.83-2.64)
1.63 (1.33-1.98)

198 (8.4)
4.0 (3.5-4.6)
Reference
Reference

265 (11.0)
5.2 (4.6-5.9)
1.27 (1.06-1.54)
1.13 (0.93-1.37)

284 (19.0)
9.5 (8.5-10.7)
2.28 (1.88-2.76)
1.68 (1.36-2.07)

716 (30.4)
16.6 (15.4-17.8)
Reference
Reference

927 (38.4)
21.5 (20.2-22.9)
1.29 (1.17-1.43)
1.26 (1.14-1.40)

820 (55.0)
35.5 (33.1-38.0)
2.10 (1.89-2.34)
1.89 (1.69-2.12)

145 (6.2)
2.8 (2.4-3.3)
Reference
Reference

187 (7.7)
3.5 (3.0-4.0)
1.22 (0.97-1.52)
1.04 (0.83-1.30)

160 (10.7)
4.8 (4.1-5.6)
1.68 (1.32-2.13)
1.29 (1.00-1.67)

288 (12.2)
5.6 (5.0-6.3)
Reference
Reference

401 (16.6)
7.4 (6.7-8.2)
1.32 (1.13-1.53)
1.13 (0.97-1.33)

334 (22.4)
10.0 (9.0-11.2)
1.77 (1.50-2.10)
1.45 (1.21-1.73)

29

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Total HF events or cardiovascular deathNo. of events
RR (95% CI)*RR (95% CI)**

458
Reference
Reference

675
1.34 (1.12-1.60)
1.17 (0.98-1.39)

728
2.31 (1.92-2.76)
1.68 (1.39-2.02)

CI, confidence interval; FI, frailty index; HF, heart failure; HR, hazard ratio; RR, rate ratio.
*Stratified by diabetes status and adjusted for treatment assignment.
**Stratified by diabetes status and adjusted for treatment assignment, age, sex, geographical region, a history of HF hospitalization, HF duration, log of Nterminal pro-B-type natriuretic peptide, left ventricular ejection fraction, and New York Heart Association.

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Table 3. Effects of Dapagliflozin Compared With Placebo on Outcomes According to Frailty Index
Outcome

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Primary composite outcome
No. of events (%)
Event rate per 100 person-years (95% CI)
HR (95% CI)*
Worsening HF
No. of events (%)
Event rate per 100 person-years (95% CI)
HR (95% CI)*
HF hospitalization
No. of events (%)
Event rate per 100 person-years (95% CI)
HR (95% CI)*
Cardiovascular deathNo. of events (%)
Event rate per 100 person-years (95% CI)
HR (95% CI)*
All-cause deathNo. of events (%)
Event rate per 100 person-years (95% CI)
HR (95% CI)*
Total HF events or cardiovascular deathNo. of events
RR (95% CI)*
KCCQ-TSS
Change from baseline to 4 months (95% CI)**
Placebo-corrected change at 4 months (95% CI)**
Change from baseline to 8 months (95% CI)**
Placebo-corrected change at 8 months (95% CI)**
KCCQ-OSS
Change from baseline to 4 months (95% CI)**
Placebo-corrected change at 4 months (95% CI)**
Change from baseline to 8 months (95% CI)**FI <0.210(not frail)
N=2,354
Placebo
Dapagliflozin
N=1,157
N=1,197

FI 0.211-0.310(more frail)
N=2,413
Placebo
Dapagliflozin
N=1,207
N=1,206

FI >0.311(most frail)
N=1,491
Placebo
Dapagliflozin
N=766
N=725

162 (14.0)
147 (12.3)
6.9 (5.9-8.0)
5.8 (5.0-6.8)
0.85 (0.68-1.06)

220 (18.2)
198 (16.4)
8.8 (7.7-10.0)
7.8 (6.8-9.0)
0.89 (0.74-1.08)

227 (29.6)
15.4 (13.5-17.5)
0.74 (0.61-0.91)

167 (23.0)
11.4 (9.8-13.2)

114 (9.9)106 (8.9)
4.8 (4.0-5.8)
4.2 (3.5-5.1)
0.87 (0.67-1.14)

157 (13.0)
138 (11.4)
6.3 (5.4-7.3)
5.5 (4.6-6.4)
0.87 (0.69-1.10)

183 (23.9)
12.4 (10.7-14.3)
0.69 (0.55-0.86)

124 (17.1)
8.4 (7.1-10.1)

105 (9.1)
93 (7.8)
4.4 (3.6-5.3)
3.7 (3.0-4.5)
0.83 (0.63-1.10)

144 (11.9)
121 (10.0)
5.7 (4.8-6.7)
4.7 (4.0-5.7)
0.83 (0.65-1.06)

169 (22.1)
11.3 (9.7-13.1)
0.69 (0.54-0.87)

115 (15.9)
7.7 (6.5-9.3)

77 (6.7)
68 (5.7)
3.1 (2.5-3.9)
2.6 (2.0-3.3)
0.84 (0.60-1.16)

93 (7.7)
94 (7.8)
3.4 (2.8-4.2)
3.5 (2.9-4.3)
1.03 (0.77-1.37)

91 (11.9)
5.4 (4.4-6.6)
0.79 (0.58-1.08)

69 (9.5)
4.2 (3.4-5.4)

146 (12.6)
142 (11.9)
5.8 (5.0-6.9)
5.4 (4.6-6.4)
0.92 (0.73-1.16)

201 (16.7)
200 (16.6)
7.4 (6.4-8.5)
7.5 (6.5-8.6)
1.01 (0.83-1.23)

179 (23.4)
10.5 (9.1-12.2)
0.90 (0.73-1.12)

155 (21.4)
9.5 (8.1-11.1)

246
222
0.85 (0.66-1.10)376
299
0.80 (0.64-1.01)434
0.71 (0.55-0.90)294

4.8 (3.8-5.7)
0.4 (-1.0 to 1.7)
4.3 (3.2-5.3)
1.7 (0.2-3.2)

5.1 (4.2-6.0)

5.7 (4.7-6.7)
2.2 (0.8-3.6)
5.0 (3.8-6.1)
3.1 (1.5-4.7)

7.9 (6.8-8.9)

7.8 (6.4-9.2)
3.6 (1.6-5.7)
8.9 (7.4-10.5)
1.8 (-0.5 to 4.1)

11.5 (10.0-12.9)

4.1 (3.3-5.0)
0.3 (-0.9 to 1.4)
3.8 (2.8-4.7)

4.4 (3.5-5.2)

5.5 (4.6-6.4)
1.5 (0.3-2.7)
4.8 (3.8-5.8)

7.0 (6.1-7.9)

6.7 (5.5-7.9)
3.4 (1.7-5.1)
7.6 (6.2-9.0)

10.1 (8.9-11.4)

6.0 (5.0-7.0)

5.2 (4.3-6.1)

31

8.0 (6.9-9.2)

7.1 (6.1-8.1)

P-valueforinteraction
0.40

0.25

0.46

0.44

0.69

0.57
0.016

10.8 (9.1-12.4)

10.0 (8.6-11.4)

0.021

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Placebo-corrected change at 8 months (95% CI)**
KCCQ-CSS
Change from baseline to 4 months (95% CI)**
Placebo-corrected change at 4 months (95% CI)**
Change from baseline to 8 months (95% CI)**
Placebo-corrected change at 8 months (95% CI)**

1.4 (0.1-2.8)
3.9 (3.0-4.7)
0.5 (-0.8 to 1.7)
3.6 (2.6-4.5)
1.6 (0.3-3.0)

2.3 (0.9-3.7)
4.3 (3.5-5.2)

5.1 (4.2-6.0)
2.1 (0.8-3.4)
4.3 (3.3—5.3)
2.8 (1.3-4.3)

5.2 (4.3-6.2)

2.4 (0.4-4.4)
7.2 (6.3-8.1)
7.1 (6.1-8.1)

6.5 (5.3-7.8)
3.7 (1.8-5.5)
7.4 (6.0-8.9)
2.2 (0.1-4.2)

10.2 (8.9-11.5)

0.018

9.6 (8.1-11.1)

CI, confidence interval; FI, frailty index; HF, heart failure; HR, hazard ratio; KCCQ-TSS, Kansas City Cardiomyopathy Questionnaire – Total Summary
Score; RR, rate ratio.
*Stratified by diabetes status.
**Mixed-effect models for repeated measurements adjusted for baseline value, visit (months 1, 4, and 8), randomized treatment, and interaction of treatment
and visit.

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Table 4. Adverse Events in Patients Assigned to Dapagliflozin or Placebo According to Frailty Index
FI <0.210
FI 0.211-0.310(not frail)(more frail)
N=2,350
N=2,411Adverse event
Placebo
Dapagliflozin
Placebo
Dapagliflozin
N=1,155
N=1,195
N=1,206
N=1,205
Discontinuation of study drug for any reason, N (%)
137 (11.9)
141 (11.8)
151 (12.5) 168 (13.9)
Discontinuation of study drug due to adverse event, N (%) 47 (4.1)
58 (4.9)67 (5.6)
72 (6.0)
Volume depletion SAE/DAE, N (%)
9 (0.8)7 (0.6)6 (0.5)19 (1.6)
Renal SAE/DAE, N (%)
18 (1.6)
12 (1.0)28 (2.3)
32 (2.7)
Amputation, N (%)
5 (0.4)1 (0.1)7 (0.6)7 (0.6)
Major hypoglycemia, N (%)
2 (0.2)0 (0.0)1 (0.1)4 (0.3)Diabetic ketoacidosis*, N (%)
0 (0.0)0 (0.0)0 (0.0)0 (0.0)

FI >0.311(most frail)
N=1,487
Placebo
Dapagliflozin
N=764
N=723
153 (20.0) 135 (18.7)
66 (8.6)
53 (7.3)
22 (2.9)23 (3.2)
45 (5.9)40 (4.5)
14 (1.8)
11 (1.5)
4 (0.5)4 (0.5)0 (0.0)2 (0.3)P-valueforinteraction
0.49
0.40
0.06
0.44
0.31
N/A
N/A

DAE, adverse event leading to treatment discontinuation; FI, Frailty Index; N/A, not applicable; SAE, serious adverse event. *Confirmed byindependent adjudication committee.
A total of 10 randomized patients were excluded from the safety analysis, as these were performed in patients who had undergone randomization andreceived at least one dose of dapagliflozin or placebo.
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Figure Legends

Figure 1. Cumulative incidence of outcomes according to Frailty Index

Figure 2. Effects of dapagliflozin compared with placebo on outcomes according to Frailty
Index. Hazard and rate ratios are stratified by diabetes status.

Figure 3. Effects of dapagliflozin compared with placebo on clinical events according to
Frailty Index. All hazard ratios are stratified by diabetes status.

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34

Worsening HF

HF hospitalization

Any hospitalization

Cardiovascular deathAll-cause death

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Worsening HF or cardiovascular deathWorsening HF
2.5

2.5

Worsening HF or cardiovascular death

0.4 0.6

1

Hazard ratio

1.5

P for interaction=0.11

0.2

0.2

0.4 0.6

1

Hazard ratio

1.5

P for interaction=0.27

0

.1

.2

.3

.4

Frailty Index

.5

.6

.7

0

.2

.3

.4

Frailty Index

.5

.6

.7

2.5

Total HF events or cardiovascular death

2.5

HF hospitalization

.1

1.5

P for interaction=0.11

1
0.4 0.6
0.2

0.2
0

.1

.2

.3

.4

Frailty Index

.5

.6

.7

0

.1

.2

.3

.4

Frailty Index

.5

.6

.7

.6

.7

2.5

All-cause death

2.5

Cardiovascular death

1.5

P for interaction=0.67

1
0.4 0.6
0.2

0.2

0.4 0.6

1

Hazard ratio

1.5

P for interaction=0.90

Hazard ratio

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0.4 0.6

1

Rate ratio

Hazard ratio

1.5

P for interaction=0.16

0

.1

.2

.3

.4

Frailty Index

.5

.6

.7

0

.1

.2

.3

.4

Frailty Index.5

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