5 Outcomes

The Diagnostics Advisory Committee (section 9) considered evidence from a number of sources (section 10).

How outcomes were assessed

5.1 The assessment consisted of a systematic review of the evidence on test performance and clinical‑effectiveness data for the CoaguChek XS system, the INRatio2 PT/INR monitor, the ProTime microcoagulation system and comparator tests. The ProTime microcoagulation system was in the assessment but has been removed from this guidance because it is no longer available to the NHS and its successor model is not intended for patient self‑monitoring.

Clinical effectiveness

5.2 The External Assessment Group conducted a systematic review of the evidence on the clinical effectiveness of self‑monitoring coagulation status in people on long‑term vitamin K antagonist therapy who have atrial fibrillation or heart valve disease.

5.3 Studies were included if they appeared relevant to the outcomes listed in the decision problem:

  • Intermediate outcomes:

    • time and values in therapeutic range

    • international normalised ratio (INR) values

    • test failure rate

    • time to test result.

  • Patient adherence to testing and treatment:

    • frequency of testing

    • frequency of visits to primary or secondary care clinics.

  • Clinical outcomes:

    • frequency of bleeds or blood clots

    • morbidity (for example, thromboembolic and cerebrovascular events) and mortality from INR testing and vitamin K antagonist therapy

    • adverse events from INR testing, false test results, vitamin K antagonist therapy and sequelae.

  • Patient‑reported outcomes:

    • anxiety associated with waiting time for results and not knowing current coagulation status and risk

    • acceptability of the tests

    • health‑related quality of life.

5.4 In total, 26 randomised controlled trials met the inclusion criteria and were included in this assessment. The CoaguChek system was used in 22 of the 26 trials: 9 trials used the CoaguChek S model, 4 trials used the CoaguChek XS model, 1 trial used the CoaguChek Plus model, and 2 trials used the CoaguChek model. It was unclear which model of the CoaguChek system was used in 6 of the 22 trials. In 2 of the remaining 4 trials either the CoaguChek S system or the INRatio monitor was used for INR measurement (results were not reported according to the type of point‑of‑care monitor, and the model of the INRatio monitor used in the trials was not reported). No trials that exclusively assessed the clinical effectiveness of the INRatio2 PT/INR monitor were identified. The ProTime microcoagulation system was used in the other 2 trials. In all 6 trials based in the UK, the CoaguChek system (either CoaguChek or version 'S') was used for the INR measurement.

5.5 The evidence on the clinical effectiveness of the coagulometers for monitoring coagulation status was summarised by the External Assessment Group in 3 categories: intermediate outcomes, clinical outcomes, and patient‑reported outcomes.

Performance of point‑of‑care coagulometers

5.6 The External Assessment Group did not carry out a formal evaluation of the performance of the CoaguChek system or the INRatio2 PT/INR monitor with regard to INR measurement because it was outside the scope of this assessment. However, an objective 'true' INR remains to be defined and INR determined in the laboratory is regarded as the gold standard to which all other measurement methods should be compared. Information on the precision and accuracy of these point‑of‑care coagulometers was therefore gathered from the available literature.

5.7 A systematic review by Christensen and Larsen published in 2012 assessed the precision and accuracy of currently available point‑of‑care coagulometers including CoaguChek XS, INRatio and ProTime. The authors found that the precision of CoaguChek XS varied from a coefficient of variation of 1.4% to 5.9% based on data from 14 studies. The precision of INRatio and ProTime varied from 5.4% to 8.4% based on data from 6 studies. The coefficient of correlation for CoaguChek XS varied from 0.81 to 0.98, and that for INRatio varied from 0.73 to 0.95. The review concluded that the precision and accuracy of point‑of‑care coagulometers were generally acceptable compared with laboratory‑based INR testing. The same conclusions were drawn by the Canadian Agency for Drugs and Technologies in Health report published in 2012 on point‑of‑care testing. Similarly, the international guidelines prepared in 2005 by the International Self‑Monitoring Association for Oral Anticoagulation stated that 'Point‑of‑care instruments have been tested in a number of different clinical settings and their accuracy and precision are considered to be more than adequate for the monitoring of oral anticoagulation therapy in both adults and children'.

5.8 Six studies compared the performance of CoaguChek S with that of CoaguChek XS in relation to conventional INR measurement. The studies showed a good agreement between the 2 CoaguChek models and conventional laboratory‑based testing results. However, the CoaguChek XS showed more accurate and precise results than CoaguChek S in both adults and children, especially for higher INR values (>3.5).

Evidence on intermediate outcomes

Time and values in therapeutic range

5.9 Eighteen trials (including 4 trials that used the CoaguChek XS system) reported INR time in therapeutic range although there was variation in the measures used for reporting this outcome, so pooling the data was not appropriate. Time in therapeutic range ranged from 52% to 80% for self‑monitoring and from 55% to 77% for standard care. In 15 of the 18 trials, time in therapeutic range was higher in self‑monitoring participants compared with those in standard care and, in 5 of these trials (including 2 trials using the CoaguChek XS system), the difference between intervention groups was statistically significant. Three of the UK‑based trials reported no statistically significant differences between self‑monitoring and standard care.

5.10 Twelve trials reported INR values in therapeutic range and there was variation in the measures used so pooling the data was not appropriate. In 8 of these trials, the proportion of INR values in therapeutic range ranged from 43.2% to 80.8% for self‑monitoring and from 22.3% to 72.0% for standard care. In 4 trials that reported the proportion of participants in therapeutic range, the values ranged from 53.0% to 72.9% for self‑monitoring and from 43.2% to 72.0% for standard care. Ten of the trials reported higher proportions of INR values in therapeutic range or larger proportions of participants in therapeutic range for self‑monitoring than for standard care.

5.11 Among participants with artificial heart valves, self‑monitoring resulted in a statistically significant higher INR time in therapeutic range compared with standard care. In 2 trials that included participants with atrial fibrillation, no time in therapeutic range differences were found between self‑monitoring and standard care.

Time to test result

5.12 One trial reported the time for each INR monitoring (that is, time from INR measurement to test results) and the total time spent for anticoagulant management during the 4‑month follow‑up period. The time spent for each INR measurement by self‑managed participants was statistically significantly lower (mean 5.3 minutes, standard deviation [SD] 2.6 minutes) compared with the time spent by participants receiving standard care (mean 158 minutes, SD 67.8 minutes, p<0.001). During the 4‑month follow‑up, the total time spent for anticoagulation monitoring by participants in standard care was statistically significantly higher (mean 614.9 minutes, SD 308.8 minutes) than the total time spent by participants who self‑managed their therapy (mean 99.6 minutes, SD 46.1 minutes, p<0.0001).

Patient adherence with testing

5.13 One trial reported more than 98% adherence with self‑testing and of those who did not adhere, 2 had difficulties doing the test or experienced disruption caused by hospitalisation, and 1 lost the CoaguChek meter. In another trial 75% (30/40) of participants did not report any problems with using the device and expressed willingness to continue with self‑monitoring. The remaining participants who did not adhere to the testing procedure (25%) reported difficulties with the technique or problems placing the fingertip blood drop on the right position on the test strip. This resulted in the need to use multiple strips to achieve a single reading.

Evidence on clinical outcomes

Bleeding

5.14 Twenty one trials reported a total of 1472 major and minor bleeding events involving 8394 participants. 476 major bleeding events were reported in a total of 8202 participants and 13 of these 21 trials reported 994 minor bleeding events in a total of 5425 participants. No statistically significant differences were seen between self‑monitoring participants (self‑testing and self‑management) and those in standard care for any bleeding events (relative risk [RR] 0.95, 95% confidence interval [CI] 0.74 to 1.21, p=0.66), major bleeding events (RR 1.02, 95% CI 0.86 to 1.22, p=0.80) and minor bleeding events (RR 0.94, 95% CI 0.65 to 1.34, p=0.73). The results were not affected by removing the UK‑based trials or by restricting the included trials to those assessing the CoaguChek system. Similarly, sensitivity analyses restricted to trials using the CoaguChek XS system showed no differences from the all‑trials results. A sensitivity analysis restricted to trials at low risk of bias slightly changed the estimate of effect but did not substantially impact on the findings (RR 0.59, 95% CI 0.27 to 1.30, p=0.19).

5.15 The External Assessment Group did a subgroup analysis by type of anticoagulant management therapy. No difference between self‑management and standard care for any bleeding events (RR 0.94, 95% CI 0.68 to 1.30, p=0.69) was found but there was a statistically significant higher risk in self‑testing participants than in those receiving standard care (RR 1.15, 95% CI 1.03 to 1.28, p=0.02). No statistically significant differences in the risk of major bleeding were seen between self‑management (RR 1.09, 95% CI 0.81 to 1.46, p=0.58) or self‑testing (RR 0.99, 95% CI 0.80 to 1.23) compared with standard care. When only minor bleeding events were assessed, there was a statistically significant increased risk in self‑testing participants (23%) compared with those in standard care (RR 1.23, 95% CI 1.06 to 1.42, p=0.005) but not in those who were self‑managing (RR 0.84, 95% CI 0.53 to 1.35, p=0.47).

5.16 Of the 21 trials, 2 trials enrolled participants with atrial fibrillation, 6 trials enrolled participants with artificial heart valves and 13 trials enrolled participants with mixed indication. No statistically significant subgroup differences were found for bleeding events according to the type of clinical indication or the type of control standard care.

Thromboembolic events

5.17 Twenty one trials reported 351 major and minor thromboembolic events in a total of 8394 participants. Self‑monitoring (self‑testing and self‑management) showed a statistically significant reduction in the risk of thromboembolic events by 42% (RR 0.58, 95% CI 0.40 to 0.84, p=0.004) compared with standard care. The risk reduction further increased to 48% when only major thromboembolic events were considered (RR 0.52, 95% CI 0.34 to 0.80, p=0.003). The risk of thromboembolic events substantially decreased when the analyses were restricted to non‑UK trials (RR 0.50, 95% CI 0.32, 0.76, p=0.001); to CoaguChek trials (RR 0.52, 95% CI 0.38, 0.71, p<0.0001); and to trials at low risk of bias (RR 0.38, 95% CI 0.16 to 0.92, p=0.03).

5.18 Self‑management halved the risk of thromboembolic events compared with standard care (RR 0.51, 95% CI 0.37 to 0.69, p<0.0001). In contrast, there was no statistically significant risk reduction for self‑testing compared with standard care (RR 0.99, 95% CI 0.75 to 1.31, p=0.56). The subgroup difference between self‑management and self‑testing was statistically significant (p=0.002). Self‑monitoring participants with artificial heart valves showed a statistically significant reduction in the number of thromboembolic events compared with those in standard care (RR 0.56, 95% CI 0.38 to 0.82, p=0.003). No statistically significant effect was shown among self‑monitoring participants with mixed clinical indication (atrial fibrillation, artificial heart valves, or other conditions) compared with participants receiving standard care.

Mortality

5.19 Thirteen trials reported 422 deaths due to all‑cause mortality in a total of 6537 participants. The risk reduction for all‑cause mortality was not statistically significant between self‑monitoring (self‑testing and self‑management) and standard care (RR 0.83, 95% CI 0.63 to 1.10, p=0.20).

5.20 Risk of death reduced by 32% through self‑management (RR 0.68, 95% CI 0.46 to 1.01, p=0.06) but not through self‑testing (RR 0.97, 95% CI 0.78 to 1.19, p=0.74) even though the test for subgroup differences was not statistically significant (p=0.13). Self‑monitoring halved the risk of mortality in participants with artificial heart valves (RR 0.54, 95% CI 0.32 to 0.92, p=0.02) but not in those with mixed clinical indication for anticoagulant therapy (RR 0.95, 95% CI 0.78 to 1.16, p=0.61). The subgroup difference between participants with artificial heart valves and those with mixed indication with regard to the number of deaths was statistically significant (p=0.05). No data were available from trials that enrolled participants with atrial fibrillation. Statistically significantly fewer deaths were recorded among participants who self‑monitored their therapy compared with those who were routinely managed by their GP/doctor (RR 0.52, 95% CI 0.30 to 0.90, p=0.02).

Evidence on patient‑reported outcomes

Anxiety associated with waiting time for results and not knowing current coagulation status and risk

5.21 One trial (n=28) compared self‑management with self‑testing in children and reported that 1 parent did not favour self‑management because of the increased anxiety about INR measurements.

Acceptability of the tests

5.22 Four trials conducted a questionnaire survey to assess acceptability to participants of self‑testing and self‑management using point‑of‑care devices. These trials reported high rates of acceptance for both self‑management and self‑testing (77% to 98%).

5.23 One of these trials reported that 93% of participants rated their satisfaction with regard to self‑monitoring (using either the INRatio monitor or the CoaguChek S system) as high or good. When asked about the overall relative satisfaction with the device, 43% of participants favoured the INRatio monitor, 36% the CoaguChek S system, and 21% both devices in equal way. One trial conducted in children reported that most participants (13 out of 14 participating families, 92%) opted for the CoaguChek XS device.

5.24 An unpublished review from the National Thrombosis Service in the Netherlands reported the INR values from over 5000 patients on vitamin K antagonist therapy using either the CoaguChek XS system or the INRatio2 PT/INR monitor for self‑monitoring. The review reported that the INR values within therapeutic range were comparable between the monitors. It also reported that the choice of monitor appeared to have no clinically relevant effect on the time in therapeutic range or adverse outcomes in people on long‑term vitamin K antagonist therapy.

Health‑related quality of life

5.25 Health‑related quality‑of‑life outcomes were reported in 9 trials using a variety of different measures. Four trials used Sawicki's questionnaire to measure quality of life, and substantially greater improvements in treatment satisfaction and self‑efficacy were reported in the self‑management arm compared with the standard care arm of the trials. All 4 trials reported a reduced level of distress and daily inconvenience although 1 trial reported an increased level of distress in participants who received education but did not directly monitor their anticoagulation therapy.

5.26 Two UK‑based trials reported no substantial differences in quality‑of‑life outcomes between self‑monitoring participants and those receiving standard care. One trial reported quality‑of‑life data using the UK SF‑36, the EuroQol scores and Lancaster's instrument. The other trial assessed themes that were adapted from the Lancaster tool, the SEIQol tool and a series of focus groups. Five common themes emerged from the interviews on self‑management: knowledge and management of condition and self‑empowerment, increased anxiety and obsession with health, self‑efficacy, relationship with healthcare professionals, and societal and economic cost. One trial, conducted in the Netherlands, measured quality of life in people with artificial heart valves by using the SF‑36v2. Substantial improvements in quality‑of‑life scores in the physical component summary were reported in people who self‑managed their therapy compared with those receiving standard care.

5.27 Another trial measured quality of life by means of the Health Utilities Index Mark 3. It reported a statistically significant gain in health utilities at the 2‑year follow‑up among self‑testing participants compared with those managed in high quality anticoagulant clinics (p<0.001). The same investigators also measured anticoagulant satisfaction using Duke Anticoagulation Satisfaction Scale. They found that the degree of satisfaction was higher in self‑testing participants compared with those in standard care (p=0.002).

5.28 One trial compared self‑management with self‑testing in children and provided quality‑of‑life data using the KIDCLOT PAC QL parent‑proxy (parents' quality of life and their assessment of child's quality of life) and the child teen KIDCLOT PAC QL. The 5 common themes identified were: awareness, communication, relationship between parent and child, flexibility and anxiety.

Costs and cost effectiveness

5.29 The External Assessment Group conducted a systematic review to identify existing economic analyses for self‑monitoring coagulation status. The review also sought to identify potentially relevant evidence sources to inform parameter values for the de novo economic model developed by the External Assessment Group. The de novo economic model constructed aimed to assess the cost effectiveness of self‑monitoring coagulation status using the CoaguChek XS system, the INRatio2 PT/INR monitor or the ProTime microcoagulation system. The ProTime microcoagulation system was included in the assessment but has been removed from this guidance because it is no longer available to the NHS and its successor model is not intended for patient self‑monitoring.

Systematic review of cost‑effectiveness evidence

5.30 The systematic review identified 12 relevant economic evaluations. All of these evaluations compared INR self‑monitoring strategies with standard care and were assessed against the NICE reference case by the External Assessment Group. The results of the studies included in the systematic review varied widely and showed that the cost effectiveness of self‑monitoring was dependent on a number of key factors.

5.31 The adopted perspective and the initial costs associated with self‑monitoring appeared to substantially affect the cost effectiveness. Self‑monitoring strategies appeared more favourable than standard care when a wider societal perspective was adopted, as a result of lower time costs associated with fewer health service contacts. The size of the estimates of effect applied to self‑monitoring in reducing thromboembolic and bleeding events compared with those applied to standard care also appeared to affect cost effectiveness. The 2 UK‑based evaluations applied effect estimates consistent with small or negligible differences between self‑management and usual care with respect to time in therapeutic range and adverse thromboembolic and haemorrhagic events. This resulted in a low probability of self‑monitoring being cost effective. Several studies that applied large effect estimates resulted in a high probability of self‑monitoring being cost effective.

5.32 The 2 UK‑based economic evaluations were based on data from the same trial. One evaluation adopted an NHS and wider societal perspective, and the other adopted an NHS and personal social services perspective. Self‑monitoring strategies appeared to increase the costs of INR monitoring in the short term and because these 2 evaluations applied small effect estimates, consistent with those seen in the largest UK‑based trial of patient self‑management, self‑monitoring of INR appeared unlikely to be cost effective. However, no UK‑based trials have been sufficiently powered to detect a statistically significant difference between standard INR monitoring and patient self‑monitoring in terms of major thromboembolic or haemorrhagic events. Therefore, the External Assessment Group carried out a meta‑analysis of relevant trials including evidence from a number of European trials in which standard care is similar to that provided in the UK in terms of approach, frequency of testing and the level of INR control achieved.

Economic analysis

5.33 The External Assessment Group developed a de novo economic model designed to assess the cost effectiveness of self‑monitoring (self‑managing and self‑testing) coagulation status using 2 different point‑of‑care coagulometers: the CoaguChek XS system and the INRatio2 PT/INR monitor.

Model structure

5.34 The structure of the Markov model was based on the review of published models of INR self‑monitoring and previous models evaluating the cost effectiveness of new anticoagulant drugs compared with warfarin therapy in people with atrial fibrillation. A further unpublished economic model of INR self‑monitoring was provided by the manufacturer of CoaguChek XS, and this model was also used to inform the structure of the new economic model.

5.35 The Markov model compared the alternative monitoring strategies for a hypothetical cohort of people with atrial fibrillation or an artificial heart valve, and was used to simulate the occurrence of thromboembolic and bleeding events over a 10‑year period. People with atrial fibrillation or an artificial heart valve represent the majority of people on long‑term vitamin K antagonist therapy. The model simulated transitions between the discrete health states, and accumulated costs and quality‑adjusted life years (QALYs) on a quarterly (3 month) cycle. Within each cycle, the simulated cohort was exposed to a risk of the adverse events as well as death from other causes. The adverse events included in the model were ischaemic stroke (minor, non‑disabling, and major, disabling or fatal), systemic embolism, minor haemorrhage, and major haemorrhage (intra‑cranial haemorrhage, including haemorrhagic stroke, gastrointestinal bleed, and others). A constraint was applied whereby the simulated cohort in the model could only experience 1 event per cycle.

Model inputs

5.36 The model was populated using data derived from the systematic clinical effectiveness review, other additional focused reviews to inform key parameters (for instance baseline risks), routine sources of cost data, and where necessary some study‑specific cost estimates based on expert opinion.

Costs

5.37 Data on the resource use and costs associated with the alternative monitoring strategies were informed by published literature, existing guidance, expert opinion, manufacturers' and suppliers' prices, and other routine sources of unit cost data. Some costs were informed by expert opinion where suitable data from other sources were not available.

Health‑related quality of life

5.38 The baseline utility value for people with atrial fibrillation or mechanical heart valve who were stable was taken as the baseline EQ‑5D value from trial data, 0.738. This value was applied to 65–70 year old people and adjusted by the External Assessment Group to estimate age‑specific baseline utilities in the model.

5.39 Utilities associated with acute events were applied for the 3‑month period after the event. For post‑event states with associated ongoing morbidity, the appropriate health state utilities were applied for all subsequent cycles spent in these states. Half‑cycle corrections were applied, by assuming that people experienced events on average at the mid‑point of the cycle. Thus a patient starting off in the well state and experiencing a major stroke in a given cycle of the model would accrue 6 weeks at the utility value for well and 6 weeks at the utility value for major stroke.

Base‑case analysis

5.40 For the purposes of decision‑making, the incremental cost‑effectiveness ratios (ICERs) per QALY gained were considered. The following assumptions were applied in the base‑case analysis:

  • 66.45% of standard care monitoring was done in primary care by practice nurses.

  • 60% of the cohort had atrial fibrillation and 40% had an artificial heart valve.

  • The average age of the cohort was 65 years, and 55% were male.

  • 50% of people who self‑monitored did self‑testing and 50% self‑managed.

  • The increase in the number of tests done per year with self‑monitoring was 23 (that is, 35 tests compared with 12 tests in standard care).

  • Relative treatment effects were estimated and applied separately for self‑testing and self‑management.

  • 15% of participants did not start self‑monitoring after training (training failure).

  • 10% of participants stopped self‑monitoring within a year of starting.

  • Self‑monitoring device costs were annuitized over 5 years.

  • 75% of devices were reused by another patient when a patient stopped self‑monitoring.

5.41 The results indicated that over a 10‑year period, introducing self‑monitoring would reduce the proportion of people experiencing a thromboembolic event by 2.5%, while slightly increasing the proportion having a major haemorrhagic event by 1.4%.

5.42 The predicted monitoring costs were higher with self‑monitoring compared with standard monitoring, but the total health and social care costs were similar and in some cases lower. The QALY gains were greater for self‑monitoring than standard monitoring. For all of the self‑monitoring coagulometers there was a QALY gain of 0.027 compared with standard monitoring. Self‑monitoring with the INRatio2 PT/INR monitor was £29 cheaper than standard monitoring. Self‑monitoring with the CoaguChek XS system was £37 more expensive than standard monitoring. Therefore, in the base‑case scenario, the self‑monitoring strategies compared favourably with standard care. The INRatio2 PT/INR monitor dominated standard monitoring in the analysis because it was less costly and more effective. The ICER for the CoaguChek XS system was £319 per QALY gained compared with standard monitoring. The lower cost of the INRatio2 PT/INR monitor and testing strips, coupled with the assumption of equivalent clinical effectiveness, meant that the INRatio2 PT/INR monitor also dominated the CoaguChek XS system. However, it should be noted that no direct evidence of clinical effectiveness was identified exclusively for the INRatio2 PT/INR monitor from the systematic review.

Analysis of alternative scenarios

5.43 Several scenario analyses were done by the External Assessment Group:

  • exclusive self‑testing or self‑management compared with standard monitoring in primary and secondary care

  • exclusive primary or secondary care clinic testing compared with self‑monitoring in primary and secondary care

  • different pooled risk estimates applied.

5.44 For the exclusive self‑management strategy, the INRatio2 PT/INR monitor and the CoaguChek XS system dominated standard monitoring under the base‑case assumptions, whereas for the exclusive self‑testing strategy, the ICERs were above £2 million per QALY gained compared with standard monitoring. The results also showed that for a mixed self‑monitoring strategy (50% self‑testing, 50% self‑management), the CoaguChek XS system and the INRatio2 PT/INR monitor dominated standard monitoring when exclusively carried out in secondary care. When applying the pooled relative risk estimates for adverse events (derived from all self‑monitoring studies) to both self‑testing and self‑managing participants, the cost savings and QALY gains associated with self‑monitoring increased.

5.45 The External Assessment Group carried out alternative non‑base‑case scenarios, to assess the impact of using self‑monitoring to replace standard monitoring tests (that is, no increase in the number of tests done annually). It was assumed that there was no difference in clinical effectiveness between self‑management, self‑testing and standard care. Under most of these scenarios, standard monitoring was found to be less costly than self‑monitoring. However, self‑testing and self‑management with the INRatio2 PT/INR monitor and the CoaguChek XS system dominated standard monitoring when carried out exclusively in secondary care.

5.46 Subgroup analyses showed the cost effectiveness of self‑monitoring compared with standard care, stratified by indication (atrial fibrillation and artificial heart valves) and cohort age. Self‑monitoring in a '65 years old with atrial fibrillation' cohort was estimated to cost £2574 per QALY gained when using the INRatio2 PT/INR monitor and £4160 per QALY gained when using the CoaguChek XS system, compared with standard monitoring. For a '65 years old with artificial heart valve' cohort, self‑monitoring with the INRatio2 PT/INR monitor and the CoaguChek XS system was found to be more effective and less costly (dominant) compared with standard monitoring.

5.47 A further analysis was carried out for the atrial fibrillation cohort using the baseline risks seen for participants with better INR control in standard care, assuming a constant relative risk reduction for thromboembolic events associated with self‑monitoring. As the INR time in therapeutic range increased in the control group, and the baseline risk of thromboembolic events consequently dropped, the cost effectiveness of self‑monitoring also decreased. However, the ICERs for the CoaguChek XS system and the INRatio2 PT/INR monitor only rose above £20,000 per QALY gained when the baseline time in therapeutic range was set at greater than 72.6%.

Sensitivity analyses

5.48 Deterministic sensitivity analysis showed that the model‑based findings were most sensitive to the baseline risk of thromboembolic events and the effectiveness of self‑monitoring for preventing these events. The ICERs for the self‑monitoring strategies rose above £30,000 per QALY gained when the baseline risk was set to 1.15% and the upper confidence limit for the relative risk of thromboembolic events associated with self‑management (RR 0.69) was applied. The same was found when the lower baseline risk of thromboembolic events was coupled with the upper confidence limit of the pooled relative risk for self‑monitoring (RR 0.89). It should be noted however that self‑management on its own remained cost saving under the former combined scenario.

5.49 A sensitivity analysis was also conducted to approximate the cost effectiveness of self‑monitoring for a cohort of children with an artificial heart valve on long‑term vitamin K antagonist therapy. For this analysis, the cohort age was set to 10, the baseline risk of thromboembolic events was reduced to 1.4%, and the standardised mortality ratio for all‑cause mortality after a stroke was set at 14.5. Under this scenario, self‑monitoring with the CoaguChek XS system and the INRatio2 PT/INR monitor dominated standard monitoring. However, it should be noted that the standardised mortality ratio estimated for an 18–55 year old cohort of people with artificial heart valves was applied because no robust data were identified to appropriately adjust the risk of death from all causes in children with an artificial heart valve.

5.50 Probabilistic sensitivity analyses of the base case were done to examine the uncertainty in the cost effectiveness of self‑monitoring. Self‑monitoring with the CoaguChek XS system and the INRatio2 PT/INR monitor were estimated to have an 80% and 81% probability of being cost effective if the maximum acceptable ICER was £20,000 per QALY gained, respectively. However, it should be noted that there is no direct randomised controlled trial evidence to show the clinical effectiveness of the INRatio2 PT/INR monitor.

  • National Institute for Health and Care Excellence (NICE)