The political economy of co-ordination challenges in the National Health Service: a postpositivist evaluation of diabetes policy and governance

The present PhD thesis develops and applies an evaluative methodology suited to the evaluation of policy and governance in complex policy areas. While extensive literatures exist on the topic of policy evaluation, governance evaluation has received less attention. At the level of governance, policymakers confront choices between different policy tools and governance arrangements in their attempts to solve policy problems, including variants of hierarchy, networks and markets. There is a need for theoretically-informed empirical research to inform decision-making at this level. To that end, the PhD develops an approach to evaluation by combining postpositivist policy analysis with heterodox political economy. Postpositivist policy analysis recognises that policy problems are often contested, that choices between policy options can involve significant trade-offs and that knowledge of policy options is itself dispersed and fragmented. Similarly, heterodox economics combines a concept of incommensurable values with an appreciation of the strengths and weaknesses of different institutional arrangements to realise them. A central concept of the field is coordination, which orientates policy analysis to the interactions of stakeholders in policy processes. The challenge of governance is to select the appropriate policy tools and arrangements which facilitate coordination. Via a postpositivist exploration of stakeholder ‘frames’, it is possible to ascertain whether coordination is occurring and to identify problems if it is not. Evaluative claims of governance can be made where arrangements can be shown to frustrate the realisation of shared values and objectives. The research makes a contribution to knowledge in a number of ways a) a distinctive evaluative approach that could be applied to other areas of health and public policy b) greater appreciation of the strengths and weaknesses of different forms of evidence in public policy and in particular health policy and c) concrete policy proposals for the governance and organisation of diabetes services, with implications for the NHS more broadly.

Telaprevir or boceprevir based therapy for chronic hepatitis C infection: Development of resistance-associated variants in treatment failure

The use of triple-therapy, pegylated-interferon, ribavirin and either of the first generation hepatitis C virus (HCV) protease inhibitors telaprevir or boceprevir, is the new standard of care for treating genotype 1 chronic HCV. Clinical trials have shown response rates of around 70–80%, but there is limited data from the use of this combination outside this setting. Through an expanded access programme, we treated 59 patients, treatment naïve and experienced, with triple therapy. Baseline factors predicting treatment response or failure during triple therapy phase were identified in 58 patients. Thirty seven (63.8%) of 58 patients had undetectable HCV RNA 12 weeks after the end of treatment. Genotype 1a (p = 0.053), null-response to previous treatment (p = 0.034), the rate of viral load decline after 12 weeks of previous interferon-based treatment (p = 0.033) were all associated with triple-therapy failure. The most common cause of on-treatment failure for telaprevir-based regimens was the development of resistance-associated variants (RAVs) at amino acids 36 and/or 155 of HCV protease (p = 0.027) whereas in boceprevir-based regimens mutations at amino acid 54 were significant (p = 0.015). SVR12 rates approaching 64% were achieved using triple therapy outside the clinical trial setting, in a patient cohort that included cirrhotics.

Prediction of breast cancer risk based on profiling with common genetic variants

BACKGROUND: Data for multiple common susceptibility alleles for breast cancer may be combined to identify women at different levels of breast cancer risk. Such stratification could guide preventive and screening strategies. However, empirical evidence for genetic risk stratification is lacking. METHODS: We investigated the value of using 77 breast cancer-associated single nucleotide polymorphisms (SNPs) for risk stratification, in a study of 33 673 breast cancer cases and 33 381 control women of European origin. We tested all possible pair-wise multiplicative interactions and constructed a 77-SNP polygenic risk score (PRS) for breast cancer overall and by estrogen receptor (ER) status. Absolute risks of breast cancer by PRS were derived from relative risk estimates and UK incidence and mortality rates. RESULTS: There was no strong evidence for departure from a multiplicative model for any SNP pair. Women in the highest 1% of the PRS had a three-fold increased risk of developing breast cancer compared with women in the middle quintile (odds ratio [OR] = 3.36, 95% confidence interval [CI] = 2.95 to 3.83). The ORs for ER-positive and ER-negative disease were 3.73 (95% CI = 3.24 to 4.30) and 2.80 (95% CI = 2.26 to 3.46), respectively. Lifetime risk of breast cancer for women in the lowest and highest quintiles of the PRS were 5.2% and 16.6% for a woman without family history, and 8.6% and 24.4% for a woman with a first-degree family history of breast cancer. CONCLUSIONS: The PRS stratifies breast cancer risk in women both with and without a family history of breast cancer. The observed level of risk discrimination could inform targeted screening and prevention strategies. Further discrimination may be achievable through combining the PRS with lifestyle/environmental factors, although these were not considered in this report.