Benefit assessment of drugs according to §35a SGB V

A benefit assessment of a drug according to §35a SGB V is based on a dossier of the pharmaceutical company in which the company provides the following information:

1) approved therapeutic indications 2) medical benefit

3) added medical benefit compared with an appropriate comparator therapy

4) number of patients and patient groups for whom a therapeutically relevant added benefit exists

5) cost of treatment for the SHI

6) requirements for quality-assured usage of the drug

The requirements for form and content of the dossier are outlined in dossier templates, which are a component of the G-BA’s Code of Procedure [251]. In the dossier, specifying the validity of the evidence, the pharmaceutical company must describe the likelihood and the extent of added benefit of the drug to be assessed compared with an appropriate comparator therapy. The information provided must be related both to the number of patients and to the extent of added benefit. The costs for the drug to be assessed and the appropriate comparator therapy must be declared (based on the pharmacy sales price and taking the Summary of Product Characteristics and package information leaflet into account).

The probability of the added benefit describes the certainty of conclusions on the added benefit. In the dossier, the extent of added benefit should be described according to the categories of the Regulation for Early Benefit Assessment of New Pharmaceuticals (ANV¹³) (major, considerable, minor, non-quantifiable added benefit; no added benefit proven; benefit of the drug to be assessed smaller than benefit of the appropriate comparator therapy) [94].

In the benefit assessment the validity and completeness of the information in the dossier are examined. It is also examined whether the comparator therapy selected by the pharmaceutical company can be regarded as appropriate in terms of §35a SGB V and the ANV. In addition, the Institute assesses the effects described in the documents presented, taking the certainty of results into account. In this assessment, the qualitative and quantitative certainty of results within the evidence presented, as well as the size of observed effects and their consistency, are appraised. The benefit and cost assessments are conducted on the basis of the standards of evidence-based medicine described in this methods paper and those of health economic standards, respectively. As a result of the assessment, the Institute presents its own conclusions, which may confirm or deviate from those arrived at by the pharmaceutical company (providing a justification in the event of deviation).

The operationalization for determining the extent of added benefit comprises 3 steps:

1) In the first step the probability of the existence of an effect is examined for each outcome separately (qualitative conclusion). For this purpose, the criteria for inferring conclusions on the evidence base are applied (see Section 3.1.4). Depending on the quality of the evidence, the probability is classified as a hint, an indication or proof.

2) In the second step, for those outcomes where at least a hint of the existence of an effect was determined in the first step, the extent of the effect size is determined for each outcome separately (quantitative conclusion). The following quantitative conclusions are possible: major, considerable, minor, and non-quantifiable.

3) In the third and last step, the overall conclusion on the added benefit according to the 6 specified categories is determined on the basis of all outcomes, taking into account the probability and extent at outcome level within the overall picture. These 6 categories are as follows: major, considerable, minor, and non-quantifiable added benefit; no added benefit proven; the benefit of the drug under assessment is less than the benefit of the appropriate comparator therapy.

The quality of the outcome, as well as the effect size, are essential in determining the extent at outcome level in the second step. The rationale for this operationalization is presented in the Appendix Rationale of the methodological approach for determining the extent of added

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benefit as well as in Skipka et al. [610]. The basic approach aims to derive thresholds for confidence intervals for relative effect measures depending on the effects to be achieved, which in turn depend on the quality of the outcomes and the extent categories.

It will not always be possible to quantify the extent at outcome level. For instance, if a statistically significant effect on a sufficiently valid surrogate is present, but no reliable estimate of this effect on a patient-relevant outcome is possible, then the (patient-relevant) effect cannot be quantified. In such and similar situations, an effect of a non-quantifiable extent is concluded, with a corresponding explanation.

On the basis of the case of a quantifiable effect, the further approach depends on the scale of the outcome. One distinguishes between the following scales:

 binary (analyses of 2x2 tables)

 time to event (survival time analyses)

 continuous or quasi-continuous, in each case with available responder analyses (analyses of mean values and standard deviations)

 other (e.g. analyses of nominal data)

In the following text, first the approach for binary outcomes is described. The other scales are subsequently based on this approach.

On the basis of the effect measure “relative risk”, denominator and numerator are always chosen in such a way that the effect (if present) is realized as a value smaller than 1, i.e. the lower the value, the stronger the effect.

A) Binary outcomes

To determine the extent of the effect in the case of binary outcomes, the two-sided 95%

confidence interval for the relative risk is used; if appropriate, this is calculated by the Institute itself. If several studies are pooled quantitatively, the meta-analytical result for the relative risk is used.

Depending on the quality of the outcome, the confidence interval must lie completely below a certain threshold for the extent to be regarded as minor, considerable or major. It is thus decisive that the upper limit of the confidence interval is smaller than the respective threshold.

The following 3 categories for the quality of the outcome are formed:

 all-cause mortality

 serious (or severe) symptoms (or late complications) and adverse events, as well as health-related quality of life

 non-serious (or non-severe) symptoms (or late complications) and adverse events

The thresholds are specified separately for each category. The more serious the event, the bigger the thresholds (i.e. closer to 1). The greater the extent, the smaller the thresholds (i.e.

further away from 1). For the 3 extent categories (minor, considerable, major), the following Table 5 shows the thresholds to be undercut for each of the 3 categories of quality of the outcomes.

Table 5: Thresholds for determining the extent of an effect

Outcome category All-cause

mortality

Serious (or severe) symptoms (or late complications) and adverse events, as well as health-related quality of life^a

Non-serious (or non-severe)

a: Precondition (as for all patient-reported outcomes): use of a validated or established instrument, as well as a validated or established response criterion.

b: Risk must be at least 5% for at least 1 of the 2 groups compared.

The relative risk can generally be calculated in 2 ways, depending on whether the risk refers to events or counter-events (e.g. survival vs. death, response vs. non-response). This is irrelevant for the statement on significance specified in Step 1 of the approach (conventional, non-shifted hypotheses), as in such a case the p-value of a single study is invariant and plays a subordinate role in meta-analysis. However, this does not apply to the distance of the confidence interval limits to the zero effect. To determine the extent of effect for each binary outcome (by means of content criteria under consideration of the type of outcome and underlying disease), it must therefore be decided what type of risk is to be assessed, that of an event or counter-event.

B) Time to event

The two-sided 95% confidence interval for the hazard ratio is required to determine the extent of the effect in the case of the outcome representing a time to event. If several studies are pooled quantitatively, the meta-analytical result for the hazard ratio is used. If the confidence interval for the hazard ratio is not available, it is approximated on the basis of the available information, if possible [651]. The same limits as for the relative risk are set for determining the extent (see Table 5).

If a hazard ratio is neither available nor calculable, or if the available hazard ratio cannot be interpreted meaningfully (e.g. due to relevant violation of the proportional hazard assumption), it should be examined whether a relative risk (referring to a meaningful time point) can be calculated. It should also be examined whether this operationalization is adequate in the case of transient outcomes for which the outcome of time to event was chosen.

If appropriate, the calculation of a relative risk at a time point is also indicated here.

C) Continuous or quasi-continuous outcomes, in each case with available responder analyses

Responder analyses are used to determine the extent of added benefit in the case of continuous or quasi-continuous outcomes. For this purpose, a validated or established response criterion or cut-off value is required. On the basis of the responder analyses (2x2 tables) the relative risks are calculated directly from them. According to Table 5 the extent of the effect is then determined.

D) Other outcomes

In the case of other outcomes where no responder analyses with inferable relative risks are available either, it should be examined in the individual case whether relative risks can be approximated [136] to set the corresponding thresholds for determining the extent. Otherwise the extent is to be classified as non-quantifiable.

For the third step of the operationalization of the overall conclusion on the extent of added benefit, when all outcomes are examined together, a strict formalization is not possible, as no sufficient abstraction is currently known for the value judgements to be made in this regard.

In its benefit assessment the Institute will compare the conclusions on probability and on the extent of the effects and provide a justified proposal for an overall conclusion.