ESTIMATING THE CLINICAL AND QUALITY OF LIFE BENEFITS OF ACUPUNCTURE FROM MULTIPLE PATIENT LEVEL DATA SOURCES: WHAT A PAIN!

Purpose: Economic analyses carried out to inform policy making must consider and synthesise all (relevant) evidence relating to the clinical effectiveness, patient-reported outcome measures (PROMs) and costs of the health technologies under scrutiny.  Evidence based medicine says that a quantitative synthesis of the same outcome measure from multiple IPD sources is the gold standard for deriving estimates of treatment effect, a key parameter in any evaluation model.  Unfortunately, in practice the evidence base is often multifaceted and fragmented, comprising a mix of aggregate (AD) and individual patient level data (IPD). This paper illustrates the methodological challenges encountered (and the solutions devised) by the authors in a recent economic model which assessed the value for money of acupuncture in chronic non-cancer related pain among primary care patients.

Methods: We had access to IPD (>18,000 patients) from 28 high quality Randomised Controlled Trials (RCTs) which evaluated acupuncture (versus either sham acupuncture and/or versus usual care) in three different conditions comprising headache, musculoskeletal pain and osteoarthritis of the knee.  The evidence base was chaotic, with the majority of the RCTs: (a) reporting different condition-specific (e.g. pain VAS, CMS, WOMAC) and generic PROMs (SF12, SF36, only two studies collected EQ-5D), (b) having different follow up durations, (c) failing to compare directly the relevant strategies.  We developed a suite of Bayesian MTC models for the synthesis of continuous (heterogeneous) outcomes (i.e. change in adjusted pain score, change in EQ-5D), which embedded a series of mapping algorithms to predict individual specific EQ-5D values, and correlated these to the patient adjusted standardised pain scores.  The analysis was carried out in WinBUGs using McMC methods, to fully characterise the relevant uncertainties while facilitating consistency checks between the direct and indirect evidence.

Results :  Acupuncture (net of sham) is more effective at reducing pain and increasing EQ-5D than usual care in the management of non-cancer related chronic pain in primary care.  

Conclusions:   Bayesian modelling provides a flexible framework to address the challenges posed by a messy evidence base.  The approach devised by the authors proved fruitful and facilitated a more robust assessment of the benefits of acupuncture, while (a) synthesising multiple heterogeneous outcomes, available at the IPD level; (b) mapping several PROMs onto the EQ5D; (c) controlling both for ‘sham effect’ and treatment effect modifiers.