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Anti-PCSK9 antibodies for hypercholesterolaemia: Overview of clinical data and implications for primary care.

ABSTRACT: To put data from our recent systematic review of phase 3 studies of anti-proprotein convertase subtilisin/kexin type 9 (PCSK9) antibodies into the context of clinical practice.Data from studies previously identified by a systematic review of phase 3 studies of alirocumab and evolocumab and additional references from non-systematic literature searches were used. We evaluated the hypothetical cardiovascular (CV) benefit in cases of typical patients in whom anti-PCSK9 antibodies may be recommended, using preliminary major CV event (CVE) rates from long-term clinical trials of anti-PCSK9 antibodies and from extrapolations derived from correlation between low-density lipoprotein cholesterol (LDL-C) reduction and CV benefit with other lipid-lowering therapies (LLTs).Rapid (within 1-2 weeks) and persistent (8-74 weeks) reductions in LDL-C levels were achieved with anti-PCSK9 antibodies. When combined with statins (± ezetimibe), high rates of LDL-C goal achievement were observed (41%-87% with alirocumab and 63%-100% with evolocumab). In long-term alirocumab and evolocumab studies, reductions in major CVEs of 48% and 53%, respectively, were observed. For every 38.7 mg/dL (1 mmol/L) reduction in LDL-C, a 22% reduction in relative CVE risk is predicted. Applying these assumptions to typical patients who have high-very high risk (15%-60% absolute 10-year CVE risk) and elevated LDL-C despite maximally tolerated statins, the 10-year number needed to treat with an anti-PCSK9 antibody to prevent one additional CVE varies from 4 to 26, depending on baseline LDL-C levels and residual absolute CVE risk.Anti-PCSK9 antibodies effectively lower LDL-C levels in a broad patient population. While awaiting comprehensive data from CV outcome trials, these agents should be considered in very high risk patients, such as those in secondary prevention and those with familial hypercholesterolaemia who are already receiving maximally tolerated LLTs, have not achieved their LDL-C goal and require substantial reductions in LDL-C.

SUBMITTER: Descamps OS

PROVIDER: S-EPMC5601297 | biostudies-other | 2017 Aug

REPOSITORIES: biostudies-other

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Anti-PCSK9 antibodies for hypercholesterolaemia: Overview of clinical data and implications for primary care.

Descamps Olivier S OS Fraass Uwe U Dent Ricardo R März Winfried W Gouni-Berthold Ioanna I

International journal of clinical practice 20170727 8

<h4>Objectives</h4>To put data from our recent systematic review of phase 3 studies of anti-proprotein convertase subtilisin/kexin type 9 (PCSK9) antibodies into the context of clinical practice.<h4>Methods</h4>Data from studies previously identified by a systematic review of phase 3 studies of alirocumab and evolocumab and additional references from non-systematic literature searches were used. We evaluated the hypothetical cardiovascular (CV) benefit in cases of typical patients in whom anti-P ...[more]

PMID: 28750477

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Project description:Familial hypercholesterolaemia (FH) is a common inherited disorder, causing lifelong elevated low-density lipoprotein cholesterol (LDL-C). Most individuals with FH remain undiagnosed, precluding opportunities to prevent premature heart disease and death. Some machine-learning approaches improve detection of FH in electronic health records, though clinical impact is under-explored. We assessed performance of an array of machine-learning approaches for enhancing detection of FH, and their clinical utility, within a large primary care population. A retrospective cohort study was done using routine primary care clinical records of 4,027,775 individuals from the United Kingdom with total cholesterol measured from 1 January 1999 to 25 June 2019. Predictive accuracy of five common machine-learning algorithms (logistic regression, random forest, gradient boosting machines, neural networks and ensemble learning) were assessed for detecting FH. Predictive accuracy was assessed by area under the receiver operating curves (AUC) and expected vs observed calibration slope; with clinical utility assessed by expected case-review workload and likelihood ratios. There were 7928 incident diagnoses of FH. In addition to known clinical features of FH (raised total cholesterol or LDL-C and family history of premature coronary heart disease), machine-learning (ML) algorithms identified features such as raised triglycerides which reduced the likelihood of FH. Apart from logistic regression (AUC, 0.81), all four other ML approaches had similarly high predictive accuracy (AUC > 0.89). Calibration slope ranged from 0.997 for gradient boosting machines to 1.857 for logistic regression. Among those screened, high probability cases requiring clinical review varied from 0.73% using ensemble learning to 10.16% using deep learning, but with positive predictive values of 15.5% and 2.8% respectively. Ensemble learning exhibited a dominant positive likelihood ratio (45.5) compared to all other ML models (7.0-14.4). Machine-learning models show similar high accuracy in detecting FH, offering opportunities to increase diagnosis. However, the clinical case-finding workload required for yield of cases will differ substantially between models.

Project description:BackgroundAnti-drug antibodies (ADAs) to bococizumab were detected in > 40% of subjects in the SPIRE lipid-lowering trials. The risk of cross-reactivity between anti-bococizumab antibodies and other approved anti-proprotein convertase subtilisin/kexin type-9 (PCSK9) monoclonal antibodies (mAbs) was investigated using a single-assay approach.MethodsBococizumab immunogenicity was assessed in SPIRE-HR, a 52-week study. The highest ADA titer sample from each ADA-positive subject (n = 155) was tested in vitro for cross-reactivity to alirocumab and evolocumab using a novel ADA assay approach. Additional specificity tiers within the bococizumab ADA assay against each drug were validated using recombinant PCSK9 as a surrogate cross-reactive positive control. If the highest ADA titer sample showed cross-reactivity, additional samples from that subject were analyzed. Cross-reactivity was determined by the ability of alirocumab or evolocumab to inhibit the sample signal greater than or equal to the cross-reactivity cut-points.ResultsADAs were detected in 44.0% (155/352) of bococizumab-treated subjects, and 27.0% also developed neutralizing antibodies (NAbs). Median ADA and NAb titers ranged from 276 to 526 and 8 to 12 over the course of the study, respectively. From 155 ADA-positive subjects tested for cross-reactivity, one (0.6%) subject showed weak cross-reactivity to both alirocumab and evolocumab. This cross-reactivity signal was transient (from Days 337 to 373) and undetectable at the last ADA-positive timepoint (Day 407).ConclusionA novel, single-assay approach was validated to assess the potential cross-reactivity of anti-bococizumab antibodies to alirocumab and evolocumab. In subjects who developed ADAs to bococizumab, the likelihood of clinically relevant cross-reactivity to marketed anti-PCSK9 mAbs is remote, based on the low frequency of cross-reactivity observed, which was weak in signal inhibition and transient in nature.Clinical trial registrationThe SPIRE-HR study is registered on ClinicalTrials.gov under the identifier NCT01968954.

Project description:BackgroundThe vast majority of individuals with familial hypercholesterolaemia in the general population remain unidentified worldwide. Recognising patients most likely to have the condition, to enable targeted specialist assessment and treatment, could prevent major coronary morbidity and mortality. We aimed to evaluate a clinical case-finding algorithm, the familial hypercholesterolaemia case ascertainment tool (FAMCAT), and compare it with currently recommended methods for detection of familial hypercholesterolaemia in primary care.MethodsIn this external validation study, FAMCAT regression equations were applied to a retrospective cohort of patients aged 16 years or older with cholesterol assessed, who were randomly selected from 1500 primary care practices across the UK contributing to the QResearch database. In the main analysis, we assessed the ability of FAMCAT to detect familial hypercholesterolaemia (ie, its discrimination) and compared it with that of other established clinical case-finding approaches recommended internationally (Simon Broome, Dutch Lipid Clinic Network, Make Early Diagnosis to Prevent Early Deaths [MEDPED] and cholesterol concentrations higher than the 99th percentile of the general population in the UK). We assessed discrimination by area under the receiver operating curve (AUROC; ranging from 0·5, indicating pure chance, to 1, indicating perfect discrimination). Using a probability threshold of more than 1 in 500 (prevalence of familial hypercholesterolaemia), we also assessed sensitivity, specificity, positive predictive values, and negative predictive values in the main analysis.FindingsA sample of 750 000 patients who registered in 1500 UK primary care practices that contribute anonymised data to the QResearch database between Jan 1, 1999, and Sept 1, 2017, was randomly selected, of which 747 000 patients were assessed. FAMCAT showed a high degree of discrimination (AUROC 0·832, 95% CI 0·820-0·845), which was higher than that of Simon Broome criteria (0·694, 0·681-0·703), Dutch Lipid Clinic Network criteria (0·724, 0·710-0·738), MEDPED criteria (0·624, 0·609-0·638), and screening cholesterol concentrations higher than the 99th percentile (0·581, 0·570-0·591). Using a 1 in 500 probability threshold, FAMCAT achieved a sensitivity of 84% (1028 predicted vs 1219 observed cases) and specificity of 60% (443 949 predicted vs 745 781 observed non-cases), with a corresponding positive predictive value of 0·84% and a negative predictive value of 99·2%.InterpretationFAMCAT identifies familial hypercholesterolaemia with greater accuracy than currently recommended approaches and could be considered for clinical case finding of patients with the highest likelihood of having hypercholesterolaemia in primary care.FundingUK National Institute for Health Research School for Primary Care Research.

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Anti-PCSK9 antibodies for hypercholesterolaemia: Overview of clinical data and implications for primary care.

Publications

Anti-PCSK9 antibodies for hypercholesterolaemia: Overview of clinical data and implications for primary care.

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