Universo de trabajo:

For each PSA scenario the number of transmissions by age group that resulted in clinical symptoms (whether correctly diagnosed as CJD or not), the number of life-years lost and the number of discounted QALYs lost were simulated through the mathematical model. These results were then

The epidemiological results presented are based on an individual surgical unit. Units are denoted S1 to S6 (defined in Categorisation of surgical units) to represent the combinations of the unit’s adherence to IPG196; whether or not instruments are kept moist; and whether or not it is assumed that the P96 group is infectious. It has been assumed that there are 27 units in England.

It is assumed that the answers produced will contain Monte Carlo sampling errors and that further RN streams and PSA configurations would provide more accurate answers. However, we believe that the results presented are sufficiently robust to draw conclusions. The base-case results assume that there may have been up to 15 deaths attributable to stCJD between 2005 and 2018.

Base-case results

The base-case results are provided in Table 26 and relate to the period 2019–23, as agreed with the NICE committee. The estimated values are presented in columns two to four; these are calculated using all PSA configurations (n = 509) and all RN streams (n = 27). The values of simulated deaths as a result of CJD infection, which were weighted by their likelihood that the transmissions of CJD modelled between 2005 and 2018, matched the observed data. The final column contains a value that represents the maximum value across the PSA configurations of the simulated deaths in that PSA multiplied by the likelihood of that PSA. Note that the maximum deaths across the P96 and the non-P96 group may not equal the maximum values for both the P96 group and the non-P96 group individually. The values are per surgical unit and need to be multiplied by 27 to represent values for England.

Interpretation of the base-case results

As anticipated, fewer deaths as a result of stCJD were estimated when IPG196 was followed and when residual mass was reduced. Thus, in terms of future deaths as a result of stCJD, S1 had fewer deaths than S2, which had fewer deaths than S3, and S4 had fewer deaths than S5, which had fewer deaths than S6. Furthermore, as anticipated, when the P96 group was assumed not to be infectious there were fewer projected deaths as a result of stCJD; that is, S1 had more deaths than S4, S2 had more deaths than S5 and S3 had more deaths than S6.

Those units that followed IPG196 and kept instruments moist (S1 and S4) had 0.052 and 0.038 future deaths caused by stCJD, respectively. Where IPG196 was not followed but instruments were kept moist, there was an increase in future deaths as a result of stCJD of 0.035 when the P96 group was deemed infectious from birth and 0.040 when the P96 group was not deemed infectious from birth. Assuming IPG196 was not followed, failure to keep instruments moist was associated with an increase in the estimated numbers of future deaths compared with not following IPG196 increased by 0.343 when the P96 group TABLE 26 Base-case results per surgical unita

Surgical unit

Average number of future deaths caused by infections between 2019 and 2023, total (non-P96 group/ P96 group)b Average number of future undiscounted life-years lost caused by infections between 2019 and 2023

Average number of future discounted QALYs lost caused by infections between 2019 and 2023

Maximum number of future deaths across the PSAs caused by infections between 2019 and 2023 multiplied by likelihood, total (non-P96 group/P96 group)b S1 0.052 (0.036/0.016) 1.548 0.459 0.519 (0.519/0.000) S2 0.087 (0.068/0.020) 2.699 0.874 1.741 (1.481/0.259) S3 0.430 (0.339/0.091) 12.438 4.009 4.259 (3.704/0.556) S4 0.038 (0.038/0.000) 0.741 0.275 0.519 (0.519/0.000) S5 0.078 (0.036/0.015) 2.276 0.736 1.741 (1.481/0.259) S6 0.389 (0.314/0.075) 10.809 3.485 4.259 (3.704/0.556)

a The values need to be multiplied by 27 to provide numbers for England rather than surgical units. b Numbers may appear discrepant as a result of rounding.

was deemed infectious from birth and 0.310 when the P96 group was not deemed infectious from birth. From these results, it is apparent that ensuring that instruments are kept moist has a large impact on the risk of future transmissions.

It is of note that the number of potential stCJD infections in the P96 group is not necessarily zero, even when these patients are assumed not to be infectious. This can occur when a P96 patient is infected via an operation prior to 2012, the date at which the new instrument sets for the P96 patients were introduced. Such a patient could then have a further high-risk operation while in the subclinical but infectious period, which could have infected P96 patients.

The circumstances in which the maximum future deaths predicted within the model were explored. A high number of future deaths were associated with the prevalence of CJD prions in their tissue being very low: < 1 per 200,000 people had prions in their tissue. In these PSA runs, no infectious people had entered the system between 2004 and 2018; this resulted in no infections and thus these PSA runs have a likelihood of 1 of matching the observed data. In the 2019–23 period, infectious people were simulated to have an operation in some RN streams, which resulted in infections and deaths. The number of deaths was greater where IPG196 was not followed and where instruments were not kept moist. The maximum number of future deaths multiplied by the likelihood is expected to be associated with approximately 10 times more deaths than the expectation. For completeness, the best-case scenario would be that there were no further deaths, which applies for all types of surgical unit. Uncertainty in the mean number of QALYs gained was explored as described in Exploring the

uncertainty in the results produced within the base-case analyses and Appendix 7. The width of the CI

around the mean estimate of QALY loss was estimated to be 0.25 for S1 units, 0.58 for S2 units, 2.07 for S3 units, 0.19 for S4 units, 0.58 for S5 units and 1.89 for S6 units. To explore the relationship between the number of PSA samples and the width of the CI, a randomly selected PSA was removed with the remaining 508 split into two groups of 254. The widths of the CIs for each of the two groups were 0.32 and 0.40 for S1; 0.87 and 0.78 for S2; 3.02 and 2.85 for S3; 0.25 and 0.29 for S4; 0.78 and 0.87 for S5; and 2.76 to 2.62 for S6. This indicated that approximately doubling the number of PSA configurations had led to a reduction in the width of the CIs by approximately 30%. The CIs produced from the 509 PSA configurations were not believed by the authors of this report to be large enough to endanger the conclusions of the analyses are endangered. Given this, it was believed that further reductions in the width of the CIs through running further PSAs were not required.

Scenario analyses using the base case as the foundation

Eight scenario analyses were run, with the change within a unit being assumed to happen instantly at midnight on the 31st December 2018. These scenarios comprised strategies to follow IPG196 and/or reduce the residual mass on instruments, and estimated the effect of removing the guidance on having different instrument sets for the P96 group from the remaining patients. The results of the scenario analyses are presented in Table 27. The results are presented in terms of surgical centres; these values would be needed to be multiplied by 27 in order to form estimates for England.

Interpretation of the scenario analyses results using the base case as the foundation These results are subject to Monte Carlo sampling error, particularly in relation to the RNs exhausted within a simulation. For example, in the scenario analysis that changed a unit from S2 to S1, at the start of 2019 this model run will have used significantly more RNs than a comparison with S1 alone. This is a result of the RNs required in selecting from 2012 onwards, the SIs used in an operation and the migration of instruments between sets (which is a feature of S2 but not of S1). This misalignment of RNs between runs will result in different simulated outcomes.

Despite the presence of Monte Carlo sampling error, the results generated are broadly consistent between comparable units, which offers support that the values are relatively robust. However, caution is advised in trying to interpret differences in the results of the scenario analyses (see Table 27) and

the base-case results (see Table 26), as these differences could be artefacts of the RNs selected. Significantly more computational time would be required to provide an accurate comparison of the scenario analyses and the base-case results; this was beyond the time scales of the project.

Scenario analyses using an alternative distribution of surgical unit compliance with following IPG196 and keeping instruments moist

As described in Exploring the probability that each type of surgical unit was the most cost-effective, the distribution that was assumed in relation to following IPG196 and guidance on keeping instruments moist was changed to provide an indication of the sensitivity of the epidemiological results to these parameters. The results for the expected number of QALYs lost as a result infections occurring between 2019 and 2023 are shown for the base-case and the alternative scenario in Figure 18. The results are very similar, as will be the costs associated with each strategy and, as such, no analyses of the alternative scenario will be provided as these are highly comparable to those of the base case. TABLE 27 Results of the scenario analyses per surgical unit using the base case as the foundation

Surgical unit

Average number of future deaths caused by infections between 2019 and 2023, total (not P96 group/P96 group)a

Average number of future undiscounted life-years lost caused by infections between 2019 and 2023

Average number of future discounted QALYs lost caused by infections between 2019 and 2023

Maximum number of future deaths across the PSAs caused by infections between 2019 and 2023 multiplied by likelihood, total (non-P96 group/P96 group)a S2 to S1 0.045 (0.037/0.008) 1.127 0.359 0.519 (0.519/0.000) S3 to S1 0.047 (0.039/0.008) 1.159 0.371 0.519 (0.519/0.000) S3 to S2 0.073 (0.073/0.000) 2.894 0.825 1.741 (1.481/0.259) S5 to S4 0.038 (0.038/0.000) 0.744 0.271 0.519 (0.519/0.000) S6 to S4 0.040 (0.040/0.000) 0.782 0.285 0.519 (0.519/0.000) S6 to S5 0.058 (0.058/0.000) 2.238 0.627 1.741 (1.481/0.259) S1b _{0.041 (0.041/0.000) 1.661 0.484 0.556 (0.444/0.111)} S4b _{0.037 (0.037/0.000) 1.543 0.451 0.556 (0.444/0.111)}

a Numbers may appear discrepant as a result of rounding.

b Removing the necessity for the P96 group to have to use a different instrument set.

5 4 3 2 1 0 S1 S2 S3 S4 S5 S6 QA LY s

Surgical unit type

10% : 30% : 60% 50% : 30% : 20%

FIGURE 18 Comparing the QALYs lost within the base case and when using an alternative assumption related to the distribution of surgical units following IPG196 and in keeping instruments moist. The percentages in the figure key refer to the proportion of units that are S1/S4, S2/S5 and S3/S6, respectively. S1 and S4 are assumed to follow both IPG196 and guidance on keeping instruments moist. S2 and S5 are assumed to keep instruments moist. S3 and S6 are assumed to neither follow IPG196 nor keep instruments moist.