Need of education and training of healthcare professionals on the PCSK9 inhibitors in cardiovascular disease
Bibliographic record
Abstract
This invited commentary refers to ‘Healthcare professionals’ perspectives on the use of PCSK9 inhibitors in cardiovascular disease: an in-depth qualitative study’, by G.A. Lee et al., https://doi.org/10.1093/eurjcn/zvae081. Dyslipidaemia is a modifiable risk factor for cardiovascular disease (CVD), and a main target in primary and secondary prevention of CVD. Dyslipidaemia is highly prevalent worldwide. In 2008, the global prevalence of raised total cholesterol among adults was 39% according to WHO.1 A recent Canadian study found that half of the patients aged 40 years or older who had a primary care visit had dyslipidaemia.2 The use of lipid-lowering medications in high-risk patients is recommended in all relevant CVD prevention guidelines issued by professional societies of different countries or regions. There is firm evidence that risk of CVD is directly related to the absolute reduction of LDL-C, and the higher the risk, the more benefit of lipid-lowering therapy. Currently, dyslipidaemia represents a medical area with rapid innovation of new drugs and subsequent need of updated recommendations around the world.3–5 Three key principles in lipid-lowering therapy that are suggested are ‘the earlier the better’, ‘the lower the better’, and ‘the longer the better’.6 However, studies have shown that dyslipidaemia is undertreated worldwide. Only a third of patients in Europe reach their LDL-C targets. The SANTORINI study that investigated use of lipid-lowering therapies included 9044 patients with high or very high cardiovascular risk from 14 western European countries.7 Notably, it was found that 22% of patients did not receive any lipid-lowering treatment, and only 20% achieved the LDL-C target (24% of high-risk patients and 19% of very high-risk patients).7 The DA VINCI observational study in central and eastern Europe found that among patients receiving lipid-lowering therapy, more than half did not achieve their LDL-C goals.8 The lack of intensive therapy and underutilization of lipid-lowering combination therapy has been proposed as reasons for lack of reaching therapeutic goals.9,10 Dyslipidaemia is asymptomatic in patients, and recommendations for screening are unclear. Thus, patients continue to be underdiagnosed and undertreated despite availability of effective therapies. There is a concern of inequitable pharmacologic management of dyslipidaemia in populations including women, those with lower socioeconomic status, and among indigenous people.2 Contrary to the documented effectiveness of high intensity statin therapy combined with drugs like ezetimibe and PCSK9 inhibitors, physicians tend to deescalate the statin dose when they add ezetimibe or a PCSK9 inhibitor.6 There are also reports of reduced adherence to statins after starting PCSK9 inhibitors.11 The need of intense treatment of dyslipidaemia among high-risk patients is challenging for other reasons. In a study of more than 2000 patients (age ≥ 65) with dyslipidaemia, most of the study sample had hypertension (84%) and diabetes (62%), and around 80% had polypharmacy.12 Thus, the intensity and goals of lipid-lowering therapy must be seen in the context of patients with several chronic conditions and drugs, and clinical challenge is not sufficiently addressed in guidelines and product monographs. Recently, Lee et al.13 published their findings on healthcare professionals’ perspectives on use of PCSK9 inhibitors. PCSK9 inhibitors are novel injectable lipid-lowering drugs that are administrated subcutaneously, preferentially by the patients themselves. The researchers performed in-depth interviews with 38 healthcare professionals (HCPs) from the UK and Italy, aiming to identify education and training needs among HCPs, and facilitators and barriers relating to use of PCSK9 inhibitors in clinical practice. HCPs were physicians, pharmacists, nurses, and a pharmacy technician involved in lipid-lowering therapy. Four themes emerged from thematic analysis of the interviews including: (i) clinicians’ previous experiences with injectable therapies; (ii) challenges with patients’ behaviours and beliefs; (iii) clinicians’ knowledge of injectable therapies and therapeutic inertia; and (iv) organizational and governance. Participants in this qualitative study described several significant barriers that could hamper the identification of eligible patients and medicine optimization. An urgent need of educational material was highlighted. Healthcare professionals are the main medium to achieve medication adherence among patients. The study from Lee et al.13 raises the question if we ignore the need for targeted medicine information to relevant HCPs when new drugs are launched. Clinicians only spend a few minutes pursuing drug-related questions that arise in clinical care, and provision of independent drug information on PCSK9 inhibitors by drug information centres can help individual HCPs.14 Academic detailing campaigns, which have proved effective in educational purposes of rational drug therapy, could reach many HCPs.15 Finally, local e-learning courses could be developed to improve delivery and optimization of PCKS9 inhibitors, as requested/wanted by the participants in the study. We expect that development of new drugs in dyslipidaemia will include new biological substances, infrequent and parenteral administration, and administrated by the patients. This model is regarded as optimal in treatment of an asymptomatic condition like dyslipidaemia where adherence issues (e.g. statins) are a challenge. Furthermore, it is in concordance with a health policy that promote simplified medication regimes and patient participation.16 The perceptions among HCPs of PCSK9 inhibitors described by Lee et al. are thus relevant in modern pharmacotherapy. The authors remind us that the study is limited to the UK and Italy, and that other countries could have revealed different themes and barriers due to different organization of lipid-lowering care. We support the idea that education and educational material should target key HCPs in a local setting. As mentioned by the participants, there is probably existing experience with interventions to overcome barriers from diabetes care. Finally, HCPs should be empowered to participate in shared decision-making with patients and their families. This research did not receive any grant from funding agencies in the public, commercial, or non-profit sector. No new data were generated or analysed in support of this research.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".