Value Assessment: Building Payercentric value propositions to inform decision-making

Transcription

1 Value Assessment: Building Payercentric value propositions to inform decision-making Aris Angelis and Panos Kanavos Medical Technology Research Group, LSE Health Advance-HTA dissemination workshop, Santiago, 9 September 2015

2 Acknowledgements This presentation has been prepared in the context of Advance-HTA, which has received funding from the European Commission, DG Research.

3 Outline Objective What is a Value Proposition? How can payers/insurers compile and use it? What evidence is required and what are the caveats? Case study of an oncology indication Conclusions

4 Objective Payers and HTA agencies need to be convinced about clinical- and cost-effectiveness, i.e. if the new therapy represents good value for money. To outline and discuss the range of criteria that can inform coverage decisions both when HTA is used as the primary criterion and when HTA is one of the criteria used in decision-making

5 Payer-centric Value Proposition In negotiating with manufacturers, payers need to compile a detailed understanding of the value and implications of a new technology This can be achieved through a patient-centric value proposition A strong payer-centric Value Proposition will contain compelling evidence that Showcases all traditional dimensions of value (therapeutic, safety and economic benefits) Translates the clinical profile into a compelling cost/effectiveness ratio Investigates the full impact of the innovation to payers and HTAs Uses comprehensive and good quality evidence Leverages critical value dimensions with a view to constructing tailormade market access plans

6 Criteria clusters to aid coverage decisions High quality evidence is needed in order to minimise uncertainty The broad criteria clusters to aid coverage decisions should have the following evidence structure: Burden of Disease (severity, unmet clinical need) Therapeutic benefit (including primary and secondary endpoints from pivotal trials) Safety and tolerability (including adverse events and toxicities) Product innovation (including patient convenience, MoA, likely spillover effects) (Socio-) Economic and budget impact (including any economic evaluation data)

7 Internal validity Internal validity refers to the extent at which an observed effect can be attributed to the intervention under investigation Internal validity depends on the study s design, conduct and analysis and main features include those of appropriate samples, sufficient follow-ups and suitable outcome measures Methodological flaws can increase the risk of bias, leading to divergence from the true treatment effect Blinding, random allocation and its concealment are recognised as keystones of internal validity, known to reduce risk of bias

8 External validity The issue of external validity of evidence is mainly caused due to the issue of generalisability that arises because of the gap between efficacy (RCTs) and effectiveness (pragmatic trials) data, i.e. ideal conditions vs. routine clinical practice External validity is primarily determined by the study design and conduct It is affected by multiple factors of which one of the most important is patient characteristics; other factors include choice of outcomes/endpoints used and adverse events assessed, drug regimen and mode of administration, patient compliance, study duration, sample sizes, costs etc.

9 Addressing evidence validity If significant internal and external validity considerations are evident, suggesting that the true treatment effect may be not aligned with the one supported by the manufacturer, and/or that it cannot be observed in real clinical settings, the regulator may request additional data and studies: (a) of an amended design that correct such methodological flaws to reveal corrected effects (b) possibly involving updated patient inclusion and exclusion criteria, more relevant outcome measures, or longer follow-up period to reveal more realistic effects.

10 Payer preferences Critical elements of evidence that payers may require include: Relevant comparator (head-to-head) Long time horizon Real-life conditions Statistical superiority

11 Payer preferences Relevant comparator (head-to-head) Relevant comparator (head-to-head) Although superiority may be shown against placebo or BSC on all primary- and secondary endpoints, it may deter payers from considering the improvement as being major. Payers prefer to see head to head (H2H) trials where the technology under consideration is compared against another active treatment. In the absence of H2H data, payers would need to see data for detailed indirect comparison across the primary and secondary endpoints that incorporate any difference in trials.

12 Payer preferences time horizon, real life data, superiority Time horizon: If it is not long enough to capture full clinical- and economic impact of disease payers may demand long-term (real life) data possibly as part of postmarketing authorization studies involving the use of registries and continuing data collection Real-life conditions: Clinical- and cost effectiveness data in real-world vs. a clinical setting Statistical superiority: E.g. for the case of acute disease, a non-significant claim on overall survival will negatively impact the value perception for payers. Without a clear statistical superiority claim for overall survival, payers will consider new therapies at most comparable to existing ones despite new therapies showing considerable additional benefits on other attributes

13 Value Proposition In a nutshell The Value Proposition (VP) for a new medical technology essentially consists of a series of value statements relating to its (superior) performance in the context of a particular disease indication, being accompanied by the necessary evidence to support them. The value statements span the widest possible range of value drivers for which the new technology is superior, or at least comparable, to the relevant comparators of interest. Main value drivers include therapeutic benefit, safety and tolerability, product innovation level and efficiency (i.e. value for money) value dimensions.

14 Building a Value Proposition Compiling the available evidence A systematic literature review should be undertaken, with a fully transparent study protocol detailing the research questions and the actual variables of interest. For example, for the case of clinical evidence (therapeutic and safety) the relevant patient population, interventions comparators, outcomes and study designs to be analysed should be ideally specified. Methodological details should be supplied on how the evidence was identified, selected, extracted but also possibly synthesised, for the case that an indirect comparison approach needs to be adopted.

15 Building a Value Proposition Compiling the available evidence Evidence identification The evidence sources searched, including any electronic databases, peer review journals, conference proceedings etc., but also the precise search strategy used, including the different combinations of keywords. Evidence selection The explicit inclusion and exclusion (i.e. eligibility) criteria directing how to accept or reject the identified evidence. Evidence extraction The methodological process adopted by the reviewers to extract the selected evidence, including any existing extraction templates, their number, their disagreement resolving approach, and any quality assessment procedure adopted.

16 Building a Value Proposition Oncology indication example Value Proposition Overall Statement New Drug is the oral option for treating metastatic colorectal cancer in adults that delivers comparatively superior medical/therapeutic and economic benefits with fewer safety and tolerability trade-offs Superior Value Profile relative to its competitor(s) Relative to current standard of care in colorectal cancer, New Drug should be considered as the product-of-choice because it Is a First-in-class for advanced colorectal cancer treatment Offers the best and most effective standard of care with fewer safety and tolerability trade-offs Provides the best improvement in patient reported outcomes Offers a superior usefulness profile across all available treatment options and Represents the best value-for-money among existing alternatives Ultimately Based on the unique value profile, New Drug s placement in the treatment of advance colorectal cancer should be first line, before all the other currently available options

17 Value Drivers - Therapeutic Evidence Key messages Primary endpoint: Overall Survival (vs. BSC) NEW DRUG prolongs survival by a median of 4.8 months vs. BSC Full population NEW DRUG reduces the risk of death by 37 % vs. BSC Steroid population NEW DRUG reduces the risk of death by 30 % vs. BSC Non-steroid population NEW DRUG reduces the risk of death by 51 % vs. BSC Primary endpoint: Overall Survival (vs. OLD DRUG) In indirect comparison between NEW DRUG and OLD DRUG using the Bucher method: Full population There is no significant difference in median overall survival (OS) Steroid population There is no significant difference, NEW DRUG is noninferior to OLD DRUG Non-steroid population There is significant difference, NEW DRUG is superior to OLD DRUG By extrapolating the individual survival curves using Weibull parametric fits and correcting for a different placebo effect, NEW DRUG prolongs statistically survival vs. OLD DRUG by a mean of 2.15 months Supporting evidence OS, (median) Months (95% CI) = 15.5 ( not reached) vs ( ) HR for death (95% CI) = 0.73 ( ) HR for death (95% CI) = 0.60 ( ) HR for death (95% CI) = 0.39 ( ) HR (95% CI) = ( ) HR (95% CI) = ( ) HR (95% CI) = ( ) Months (95% CI) = ( )

18 Value Drivers - Therapeutic Evidence Key messages Evidence NEW DRUG Evidence BSC Level of significance Secondary endpoints (vs. BSC) NEW DRUG shows superiority vs. BSC in all secondary endpoints of disease progression including: Radiographic progression free survival (rpfs); (median) mo. Full population Steroid population Non-steroid population 7.1 ( ) 1.9 ( ) HR = 0.45 ( ) HR = 0.65 ( ) HR = 0.31 ( ) Modified progression free survival (mpfs); (median) mo. Full population Steroid population Non-steroid population Time to first SRE (TTF SRE); (median) mo. Biomarker response ( 50% from baseline); % of patients HR = 0.51 (0.45, 0.58) HR = 0.62 ( ) HR = 0.40 ( ) 15.6 ( ) 12.4 (8.9 - NR) HR = 0.59 ( ) 51.0% 2.5% OR = ( ) Biomarker progression; (median) mo. 7.3 ( ) 2.0 ( ) HR = 0.35 ( ) Risk of biomarker progression -65% Objective radiographic response (ORR) 26.9% 2.8% OR = 10.2 ( )

19 Value Drivers - Therapeutic Evidence Key messages Evidence NEW DRUG Evidence OLD DRUG Level of significance Secondary endpoints (vs. OLD DRUG) NEW DRUG shows superiority or comparability vs. OLD DRUG in several secondary endpoints of disease progression including: Radiographic progression free survival (rpfs); (median) mo. Full population Steroids population Non-steroids population Modified progression free survival (mpfs); (median) mo HR = 0.66 ( ) HR = 0.95 ( ) HR = 0.50 ( ) 6.8 HR = 0.78 ( ) TTF SRE mo HR = 1.18 ( ) TTF SRE incidence; % of patients 30.9% 23.6% OR = 1.05 [0.81; 1.40] Biomarker response ( 50% from baseline); % of patients 51.0% 35.0% OR = ( ) Objective radiographic response (ORR) 26.9% 15.8% OR = 2.54 ( )

20 Value Drivers - HRQOL Evidence Key messages Evidence NEW DRUG Evidence BSC Level of significance Patient reported outcomes (vs. BSC) NEW DRUG is associated with a delay in deterioration of QoL by 6.5 months vs. BSC 10.6 ( ) months 4.1 ( ) months HR= 0.55 (95%CI [0.47, 0.68]; P<0.001 The treatment effect favoured NEW DRUG vs. BSC at all visits between Week 4 and Week 25 No significant changes from baseline until Week 25 Significant decrease (worsening) from baseline at Week 4, 8, 16 and 25 Key messages Evidence NEW DRUG Evidence OLD DRUG Level of significance Patient reported outcomes (vs. OLD DRUG) Difficult to make a robust claim currently as there are no comparable endpoints

21 Value Drivers - Safety Evidence Key messages Safety (vs. BSC) NEW DRUG is well tolerated. Its safety profile is comparable to BSC including similar or improved safety in regards to: Evidence NEW DRUG Evidence BSC Any adverse events (AEs); % of patients 92.1% 91.3% Adverse drug reactions (ADRs), ie AEs possibly, probably or definitely attributed to the drug 64.5% 62.2% Serious AEs 30.1% 33.8% Time to treatment discontinuation (TTTD); (mean) months Level of significance Full population Steroid population Non-steroid population AEs causing treatment discontinuation; (% of patients) 8.61 (±0.18) 3.52 (±0.22) AEs leading to death 3.8% 3.2% HR = 0.44 ( ) HR = 0.59 ( ) HR = 0.34 ( ) 7.1% 9.7% OR = 0.86 (0.50; 1.16)

22 Value Drivers - Safety Evidence Key messages Safety (vs. OLD DRUG) NEW DRUG has a tolerability and a safety profile that is comparable to OLD DRUG, including all specific AEs of all grades, except for bone pain. Time to treatment discontinuation (TTTD); (mean) months Treatment discontinuation due to an AE (% of patients) Evidence NEW DRUG Evidence OLD DRUG Level of significance/ Justification 8.61 HR = 0.75 ( ) 7.1% 14.2% OR: [0.751; 1.788] Bone pain Higher likelihood Lower likelihood OR: 1.85 [ ]) (p.s. concomitant corticosteroids are used in the case of OLD DRUG) Importantly, there is a difference in toxic effects, favouring NEW DRUG: Hepatotoxicity (requiring regular liver function testing) Absent Present Due to the different MoA

23 Value Drivers - Patient Convenience Key messages Usefulness profile (vs. BSC) NEW DRUG can be taken orally, does not have to go through the toxic IV chemo process as part of BSC; allows patients to be treated at home NEW DRUG is more convenient to take with limited special instructions for administration compared to BSC Usefulness profile (vs. OLD DRUG) NEW DRUG is more convenient to take with limited special instructions for administration compared to OLD DRUG NEW DRUG is associated with less monitoring requirements compared to OLD DRUG Supporting evidence NEW DRUG are administered as capsules through an oral RoA compared to BSC which is administered intravenously under hospital settings NEW DRUG can be taken on full stomach, without the need for concomitant corticosteroids compared to BSC NEW DRUG can be taken on full stomach, without the need for concomitant corticosteroids compared to OLD DRUG that needs to be administered on empty stomach and in combination with corticosteroids NEW DRUG needs outpatient monitoring every 8 weeks compared to OLD DRUG which needs every 4 weeks due to the risk of hepatotoxicity and increased blood pressure associated with OLD DRUG

24 Value Drivers - Value For Money Key messages Value-for-money (vs. BSC) NEW DRUG is the most cost effective treatment options in advanced colorectal cancer, using economic evaluation data At Base case From extensive scenario analyses and deterministic and probabilistic sensitivity analysis showing that the model is robust NEW DRUG reduces the cost burden of disease vs. BSC? Value-for-money (vs. OLD DRUG) NEW DRUG is the most cost effective treatment options in advanced prostate cancer, using economic evaluation data At Base case From extensive scenario analyses and deterministic and probabilistic sensitivity analysis showing that the model is robust Using OS and rpfs data respectively: NEW DRUG I reduces the cost burden of disease vs. OLD DRUG Supporting evidence The base case incremental cost effectiveness ratio (ICER) for NEW DRUG was 40,587 against BSC There is a 85% probability of being cost-effective against BSC at a WTP of 50,000 per QALY gained, a threshold previously used for the recommendation of OLD DRUG (Life extending, end of life treatment eligibility criteria include i) treatment indication is for patients with less than 24 months life expectancy, ii) treatment offers a life extension of at least 3 months, and iii) treatment is licensed/indicated for small patient populations) Need to develop cost/minimization scenarios to the Payers in the study countries The base case incremental cost effectiveness ratio (ICER) for NEW DRUG was 15,195 against OLD DRUG There is a 81% probability of NEW DRUG being cost-effective against OLD DRUG at a willingness to pay (WTP) of 20,000 per QALY gained, and 99% at a WTP of 30,000 per QALY gained NEW DRUG is associated with an ICER of 1,505 for each additional month of survival and with an ICER of 1,251 for each additional month of progression free survival Assuming equal overall survival, time to treatment discontinuation and drug acquisition cost, while including the difference in monitoring costs and requirement for steroids, there is a cost saving of 1,050 while resulting in the same number of QALYs

25 Comparative presentation of value drivers Value drivers Efficacy Overall Survival (OS) Overall Survival (OS) Skeletal Related Effects (SRE) Skeletal Related Effects (SRE) Objective Response Rate (ORR) Radiographic Progression Free Survival (rpfs) Modified Progression Free Survival (mpfs) Biomarker Response Time to treatment discontinuation (TTTD) Radiographic Progression Free Survival (rpfs) Biomarker Progression Median Mean Time to first Incidence Median time to Median time to Patients proportion Patient proportion free of progression Patient proportion free of progression Skeletal Related Effects (SRE) Rate? Biomarker Progression Median time to? Safety Adverse events Tolerability Hypokalemia Hepatotoxicity Adverse events Bone pain? Innovation Mechanism of Action (MoA) Patient convenience Socioeconomic Direct medical costs Value for money Value for money Special instructions Outpatient visits Cost effectiveness Cost minimisation NEW DRUG vs. OLD DRUG Inferior Not stat. dif. Superior??

26 Key Takeaways for insurers and HTAs Building a value proposition requires a range of performance indicators across all critical value dimensions of the drug Additional data may be required to ensure satisfactory internal and external validity All stages of evidence collection, analysis, and interpretation should be informed based on payer preferences Evidence should be identified, selected, extracted, and synthesised using a fully transparent study protocol A comparative presentation of value drivers should be included in the summary of the results

27 Health Insurer s Point of View Health Insurers may be willing to confirm the content of the Value Proposition or build their own version reflecting their own perspective. Based on this payers can judge whether a new therapy is inferior, not statistically different or superior to a comparator Most data required should be available in the (peer reviewed) literature If not published their credibility could be questioned Insurers may conduct their own (systematic) literature review(s) to ensure all critical evidence is incorporated Other sources may be required for the collection of real world effectiveness data and resource use (cost of illness) data Registries and observational studies

28 Thank you! Aris Angelis Panos Kanavos Aris Angelis & Panos Kanavos, 2015