4 Evidence

The diagnostics advisory committee (section 8) considered evidence on virtual chromoendoscopy for real-time assessment of colorectal polyps during colonoscopy from several sources. Full details of all the evidence are in the committee papers.

Clinical effectiveness

4.1 In total, 30 studies were included in the systematic review. There were 24 studies on Narrow Band Imaging (NBI), 3 studies on flexible spectral imaging colour enhancement (FICE) and 5 studies on i‑scan. Two studies included more than 1 technology (1 study on NBI and FICE; and 1 study on NBI and i‑scan). Fourteen studies were done in the US, 11 in Europe (of which, 4 were in the UK), 4 in Asia and 1 in Australia. Most of the studies were carried out in specialist centres. The QUADAS assessment found that all studies were at low risk of bias.

4.2 None of the included studies reported on health-related quality of life, mortality, incidence of colorectal cancer, or number of outpatient appointments.

Virtual chromoendoscopy using Narrow Band Imaging

4.3 Twenty-four studies reported on the use of NBI. Most were done in a single centre and the results might not be generalisable to other centres. The endoscopists' levels of experience of using NBI varied: all endoscopists were experienced in 8 studies, some had experience in 4 studies, none had experience in 4 studies, and the experience levels were unclear for 8 studies.

Accuracy of Narrow Band Imaging for characterising diminutive colorectal polyps in the whole colon

4.4 Seventeen studies reported on the sensitivity of NBI and 16 studies reported on the specificity of NBI for characterisations of polyps made with any level of confidence. The sensitivity ranged from 0.55 to 0.97 and the specificity ranged from 0.62 to 0.95. Bivariate meta-analysis of the 16 studies reporting on both sensitivity and specificity produced summary values of 0.88 (95% confidence interval [CI] 0.83 to 0.92) for sensitivity and 0.81 (95% CI 0.75 to 0.85) for specificity.

4.5 The sensitivity and specificity of NBI was higher for polyps diagnosed with high confidence, compared with those diagnosed with any level of confidence (that is, those assessed with low and high confidence). Eleven studies reported on the sensitivity and specificity of NBI for assessing polyps that were characterised with high confidence. Bivariate meta-analysis produced summary values of 0.91 (95% CI 0.85 to 0.95) for sensitivity and 0.82 (95% CI 0.76 to 0.87) for specificity.

4.6 A post-hoc bivariate meta-analysis was run for high-confidence characterisations, which only included studies with endoscopists who were experienced in using NBI (4 studies). The analysis produced summary values of 0.92 (95% CI 0.89 to 0.94) for sensitivity and 0.82 (95% CI 0.72 to 0.89) for specificity. Compared with the analysis for endoscopists with different levels of experience, the point estimate for sensitivity increased slightly from 0.91 to 0.92 and the specificity did not change. The confidence interval for sensitivity narrowed for experienced endoscopists compared with that for endoscopists with a variety of experience. The confidence interval for specificity for experienced endoscopists widened (0.72 to 0.89) compared with endoscopists with different levels of experience (0.76 to 0.87).

4.7 Sixteen studies reported on the negative predictive value of NBI for characterising diminutive polyps in the whole colon, made with any level of confidence. The negative predictive value ranged from 43% to 96%. The lower bound of the 95% confidence interval fell below 90% in all studies, apart from Patel et al. (2016).

4.8 Thirteen studies reported on the negative predictive value for high-confidence characterisations of polyps in the whole colon. The negative predictive value was higher for characterisations made with high confidence compared with those made with all levels of confidence. The range was 48% to 98%. When reported, the lower bound of the 95% confidence interval fell below 90% in all but 2 studies.

4.9 One study looked at the difference between the negative predictive value of characterisations done by specialists in colonoscopy and general endoscopists. The study found that specialists achieved a higher negative predictive value (90.9%; CI 70.8 to 98.9) than generalists (71.4%; 95% CI 47.8 to 88.8). However, the difference was not statistically significant.

Accuracy of Narrow Band Imaging for characterising polyps in the rectosigmoid colon

4.10 Four studies reported on the sensitivity and specificity of NBI for assessing polyps in the rectosigmoid colon with high confidence and 3 studies reported data for assessing polyps in the rectosigmoid colon with any level of confidence. Bivariate meta-analysis for characterisations made with any level of confidence produced summary values of 0.85 (95% CI 0.75 to 0.91) for sensitivity and 0.87 (95% CI 0.74 to 0.94) for specificity. For characterisations made with high confidence, summary values were 0.87 (95% CI 0.80 to 0.92) for sensitivity and 0.95 (95% CI 0.87 to 0.98) for specificity.

4.11 A post-hoc bivariate meta-analysis was run for the 2 studies that included endoscopists who were experienced in using NBI. For high-confidence characterisations, it produced summary values of 0.90 (95% CI 0.71 to 0.97) for sensitivity and 0.98 (95% CI 0.91 to 1.00) for specificity. When compared with the bivariate analysis for endoscopists with different levels of experience, the point estimate for sensitivity increased from 0.87 to 0.90 and the point estimate for specificity increased from 0.95 to 0.98. The confidence interval for sensitivity widened for experienced endoscopists (0.71 to 0.97) compared with that for endoscopists with different levels of experience (0.80 to 0.92). The confidence interval for specificity narrowed slightly for experienced endoscopists (0.91 to 1.00) compared with that for endoscopists with different levels of experience (0.87 to 0.98).

Other outcomes for Narrow Band Imaging

4.12 Thirteen studies reported on the agreement between surveillance intervals set when using NBI compared with those set by histopathology; agreement ranged from 84% to 99%.

Virtual chromoendoscopy using flexible spectral imaging colour enhancement

4.13 Three studies reported on the use of FICE. All studies were carried out in single centres and none reported on high-confidence characterisations of diminutive polyps or on a specific part of the colon. One study reported that the endoscopists did not have any experience of using FICE. In the remaining 2 studies, it was unclear whether the endoscopists had any experience.

Accuracy of flexible spectral imaging colour enhancement for characterising diminutive colorectal polyps in the whole colon

4.14 All 3 studies reported the sensitivity and specificity of FICE for characterising polyps in any part of the colon. The sensitivity ranged from 0.74 to 0.88 and the specificity ranged from 0.82 to 0.88. Bivariate meta-analysis using all 3 studies produced summary values of 0.81 (95% CI 0.73 to 0.88) for sensitivity and 0.85 (95% CI 0.79 to 0.90) for specificity. The negative predictive values ranged from 70% to 84%.

Virtual chromoendoscopy using i‑scan

4.15 Five studies reported on the use of i‑scan. Most of the studies were done in a specialist endoscopy centre by 1 endoscopist. So, it is unclear how generalisable the results are to different settings. Three studies reported that the endoscopists had experience of using i‑scan. The remaining 2 studies did not report on level of experience.

Accuracy of i‑scan for characterising colorectal polyps in the whole colon

4.16 Two studies reported on high-confidence characterisations of polyps in the whole colon. Bivariate meta-analysis produced summary values of 0.96 (95% CI 0.92 to 0.98) for sensitivity and 0.91 (95% CI 0.84 to 0.95) for specificity.

4.17 Two studies reported that the negative predictive value of i‑scan for detecting colorectal polyps in the whole colon was above 90%. But, the lower bound of the confidence interval for both studies was below 90%.

Accuracy of i‑scan for characterising polyps in the distal or rectosigmoid colon

4.18 Two studies reported that the negative predictive value of i‑scan for detecting colorectal polyps in the distal or rectosigmoid colon was above 90%. But, the lower bounds of the confidence interval were below 90%.

Cost effectiveness

Review of economic evidence

4.19 Two studies were found that reported full economic evaluations comparing virtual chromoendoscopy with histopathology. Hassan et al. (2010) found no difference in life expectancy between the 2 strategies and therefore could not calculate a cost per life year gained. Kessler et al. (2011) found that the cost per life year gained for sending all polyps detected during colonoscopy for histological analysis, compared with a resect and discard strategy using virtual chromoendoscopy, was US $377,460. It is unclear how generalisable the results are to the NHS, because non-UK resource costs were used and health outcomes were not valued in quality-adjusted life years (QALYs).

Modelling approach

4.20 The external assessment group (EAG) developed a de novo economic model to assess the cost effectiveness of virtual chromoendoscopy (NBI, FICE and i‑scan) compared with histopathology for assessing colorectal polyps. The model took the perspective of the NHS and personal social services and all costs and QALYs were discounted at a rate of 3.5% per year. The model consisted of 2 parts. The first part was a decision tree that estimated the short-term costs and outcomes of the first colonoscopy. In this model, polyps are assessed and a surveillance interval is assigned. The second part was an existing model used to estimate the long-term costs and QALYs for each surveillance classification, including incorrect surveillance classifications. The second model was a state transition model developed by the School of Health and Related Research (ScHARR), at the University of Sheffield, for the NHS bowel cancer screening programme. The model was chosen because it is a long-standing model that has been validated and was used to inform the introduction of the screening programme. The model was run independently and the cost and QALY estimates were entered as parameters at the end points of the decision tree model.

Model structure

4.21 The decision tree compared the virtual chromoendoscopy strategies with a histopathology strategy. It had 4 main arms, 1 for each test that was assessed: NBI, FICE, i‑scan and standard endoscopy with histopathology. The comparator arm of the decision tree assumed that all polyps are resected and sent to histopathology and everyone is given the correct surveillance interval.

4.22 Firstly, the cohort was divided into 4 risk categories based on the number of adenomas that they have:

  • no adenomas

  • low risk (1 to 2 adenomas)

  • intermediate risk (3 to 4 adenomas)

  • high risk (5 or more adenomas).

4.23 The model then calculated the proportion of patients in each category expected to have a correct surveillance interval assigned and the proportions expected to have an incorrect surveillance interval assigned.

4.24 With a virtual chromoendoscopy strategy, the following errors could lead to an incorrect surveillance interval (too long or too short) being assigned in the model:

  • 1 or more hyperplastic polyps might be misclassified as an adenoma and so be unnecessarily resected

  • 1 or more adenomas might be misclassified as a hyperplastic polyp and left in place.

4.25 The ScHARR bowel cancer screening (SBCS) model was designed to assess the cost effectiveness of different screening strategies for colorectal cancer for a lifetime time horizon. The model simulated the progression of colorectal cancer in people who are eligible for the bowel cancer screening programme in England.

Population

4.26 The population in the base-case analysis was people taking part in the bowel cancer screening programme who had been referred for colonoscopy. Patients were included if they had at least 1 diminutive polyp (5 mm or less), and were excluded if they had 1 or more non-diminutive polyps (more than 5 mm). In addition, scenario analyses looked at:

  • people offered colonoscopy as surveillance because they previously had adenomas removed and

  • people referred to colonoscopy by a GP because of symptoms of colorectal cancer.

Diagnostic strategy

4.27 Two different diagnostic strategies were explored in the economic analyses, the virtual chromoendoscopy strategy (used in the base case) and the DISCARD strategy (Detect, InSpect, ChAracterise, Resect, and Discard; used in some scenario analyses). The criteria common to both strategies were that diminutive polyps:

  • in the whole colon are optically characterised using virtual chromoendoscopy

  • diagnosed with high confidence as adenomas are resected and discarded

  • diagnosed with low confidence are resected and sent to histopathology.

4.28 The characteristic unique to the virtual chromoendoscopy strategy was that diminutive polyps, in the whole of the colon, diagnosed with high confidence as hyperplastic are left in place.

4.29 The characteristics unique to the DISCARD strategy were that diminutive polyps:

  • in the proximal colon, characterised with high confidence as hyperplastic, are resected and discarded.

  • in the rectosigmoid colon, diagnosed with high confidence as hyperplastic, are left in place.

Model inputs of the decision tree

4.30 The model inputs were taken from various sources, including routine sources of cost data, published literature, and the clinical-effectiveness review and meta-analyses.

4.31 The prevalence of adenomas was estimated for 3 populations: the screening population (base case), the surveillance population (scenario analysis) and the symptomatic population (scenario analysis). For the base-case analysis on the screening population, the prevalence of adenomas was taken from a published study by Raju et al. (2013) that retrospectively analysed data from a US colon cancer screening programme. The distributions of adenomas and the data sources for each population are reported in table 1.

Table 1 Proportion of people by risk category for screening, surveillance and symptomatic population

Risk category

Screening population (Raju et al. 2013)

Surveillance population (Martinez et al. 2009)

Symptomatic population (McDonald et al. 2013)

No adenoma

0.302

0.533

0.782

Low risk

0.535

0.358

0.125

Intermediate risk

0.107

0.072

0.061

High risk

0.056

0.037

0.032

4.32 Data on diagnostic accuracy were taken from the clinical-effectiveness review and meta-analysis for NBI, FICE and i‑scan, as shown in table 2. Data were used for polyps in the whole colon that were characterised with high confidence in the base-case analysis for NBI and i‑scan. Data were used for polyps in the whole colon that were characterised with any level of confidence in the base-case analysis for FICE. It was assumed that the proportion of low-confidence characterisations was the same for all 3 technologies, and was calculated using data from 12 NBI studies, because data were not available for FICE and i‑scan. The comparator, histopathology, was assumed to be 100% accurate.

Table 2 Sensitivity and specificity for virtual chromoendoscopy technologies

Parameter

Value

Lower 95% CI

Upper 95% CI

Source

NBI sensitivity

0.910

0.855

0.945

Meta-analysis

NBI specificity

0.819

0.760

0.866

Meta-analysis

FICE sensitivity

0.814

0.732

0.875

Meta-analysis

FICE specificity

0.850

0.786

0.898

Meta-analysis

i‑scan sensitivity

0.962

0.917

0.983

Meta-analysis

i‑scan specificity

0.906

0.842

0.946

Meta-analysis

Proportion of polyp characterisations made with low confidence

0.214

0.21

0.22

EAG literature reviewa

a The average value from 12 NBI studies that were included in the literature review. Data were not available on the proportion of polyp characterisations made with low confidence for FICE and i‑scan.

Abbreviations: CI, confidence interval; EAG, external assessment group; FICE, flexible spectral imaging colour enhancement; NBI, Narrow Band Imaging.

4.33 The probabilities of adverse events occurring during colonoscopy were assumed to be 0.003 for hospitalisation for bleeding with polypectomy, 0.003 for perforation with polypectomy, and 0.052 for death of patients with perforation during polypectomy. These values were taken from published values used in the SBCS model.

4.34 For the base-case analysis, the costs of colonoscopy, polypectomy, adverse events and histopathology were taken from the NHS reference costs for 2014/15 (see table 3). Training costs were assumed to be £14.72 per patient, based on the assumption that endoscopists complete 150 endoscopies per year and that training costs are equivalent to 2 days of pay (£1,104) per year.

Table 3 Unit costs for colonoscopy and treating adverse events

Parameter

Value

Lower 95% CI

Upper 95%CI

Cost of colonoscopy without polypectomy

£518.36

£340.89

£695.83

Cost of colonoscopy with polypectomy

£600.16

£406.24

£794.08

Cost of treating bowel perforation (major surgery)

£2,152.77

£902.21

£3,403.33

Cost of admission for bleeding (overnight stay on medical ward)

£475.54

£327.69

£623.39

Pathology cost per polyp examination

£28.82

£6.78

£50.86

Abbreviation: CI, confidence interval.

4.35 The cost of upgrading equipment was not included in the model. It was assumed that most hospitals already had equipment with virtual-chromoendoscopy-enabled technology in place, and hospitals that do not have this equipment will get it in the future as part of standard procurement. Therefore, the base-case analysis assumes that the cost of maintaining and purchasing equipment is included in the Healthcare Resource Group (HRG) cost of colonoscopy.

4.36 Health-related quality of life was calculated in the SBCS model. The base-case analysis used utility values taken from a study by Ara and Brazier (2011). The model assumes a utility of 0.697 for people with cancer and a utility of 0.798 for people without cancer.

4.37 A scenario analysis was done using utility values from a study identified by the EAG through a targeted search (Farkkila et al. 2013). For the scenario analysis, it was assumed that the utility for people with cancer was 0.761 and for people without cancer was 0.798.

4.38 No disutility values for adverse events during polypectomy, such as bowel perforation and bleeding, were found. Therefore, the values were taken from studies that reported on similar events. A QALY loss of 0.006 was taken from Dorian et al. (2014) for the disutility of a major gastrointestinal bleed and a QALY loss of 0.010 was taken from Ara and Brazier (2011) for the disutility of bowel perforation.

4.39 The costs and QALYs for the end points of the decision tree were calculated by running the SBCS model with a cohort of patients aged 65.

Bowel cancer screening model inputs

4.40 The following changes were made to the SBCS model for this assessment:

  • Colonoscopy and adverse-event costs were updated to 2014/15 costs.

  • The screening costs were updated.

  • Adenoma recurrence rates were adjusted to model people with higher-disease risk and people with adenomas left in the body.

Base-case results

4.41 The following assumptions were applied in the base-case analysis:

  • The long-term cost and QALY outcomes were estimated using the SBCS model, which assumed that standard colonoscopy with histopathology assessment of all polyps was used for follow‑up surveillance. Therefore, diagnostic accuracy data and training costs associated with virtual chromoendoscopy were not included in the long-term results.

  • Studies did not report on the relationship between diagnostic accuracy and assigning people to the correct surveillance intervals, therefore the following was assumed:

    • diagnostic accuracy data were applied to individual polyps

    • the adenoma-to-hyperplastic-polyp ratio was assumed to be the same for each risk category.

  • Only diminutive polyps were assessed, people with polyps larger than 5 mm were not included in the model.

  • The proportion of polyps assessed with low confidence (21%) was assumed to be the same for NBI, FICE and i‑scan.

  • The disutility for bleeding was assumed to be similar to a major gastrointestinal bleed.

  • The disutility for perforation was assumed to be the same as for a stomach ulcer, abdominal hernia or rupture.

4.42 The results of the base-case analysis can be seen in table 4. Pairwise analyses compared each of the 3 technologies in turn (NBI, FICE and i‑scan) with histopathology. Results showed that NBI and i‑scan dominated histopathology, that is, they were cheaper and more effective than histopathology. FICE was cost saving and less effective than histopathology, with an incremental cost-effectiveness ratio (ICER) of £671,383 saved per QALY lost.

4.43 The differences in incremental QALYs ranged from −0.0001 when FICE was compared with histopathology to 0.0007 when i‑scan was compared with histopathology. The differences in costs ranged from −£87.70 when FICE was compared with histopathology to −£73.10 when NBI was compared with histopathology.

4.44 The lifetime risk of colorectal cancer according to the method of assessing polyps, calculated from the model, was:

  • 3.025% for histopathology

  • 3.020% for NBI

  • 3.045% for FICE

  • 3.021% for i‑scan.

4.45 The fully incremental analyses show that histopathology was dominated by NBI and i‑scan; and NBI was dominated by i‑scan. When i‑scan was compared with FICE it had an ICER of £10,466 per QALY gained.

Table 4 Cost-effectiveness results from the lifetime economic model

 

Costs

Inc

Costs

QALYs

Inc

QALY

ICER (£ per QALY)

Full incremental results

Histopathology

£988.95

11.2703

Dominated

FICE

£901.25

−£87.70

11.2701

−0.0001

i‑scan

£909.74

£8.49

11.2709

0.0008

£10,465.74

NBI

£915.85

£6.11

11.2708

−0.0001

Dominated

Pairwise comparisons

Histopathology

£988.95

11.2703

NBI

£915.85

−£73.10

11.2708

0.0005

Dominates

Histopathology

£988.95

11.2703

FICE

£901.25

−£87.70

11.2701

−0.0001

£671,383a

Histopathology

£988.95

11.2703

i‑scan

£909.74

−£79.21

11.2709

0.0007

Dominates

a Incremental cost saving per QALY lost.

Abbreviations: FICE, flexible spectral imaging colour enhancement; ICER, incremental cost-effectiveness ratio; Inc, incremental; NBI, Narrow Band Imaging; QALY, quality-adjusted life year.

Analyses of alternative scenarios

4.46 The EAG did 12 scenario analyses, and a further 2 scenario analyses were done as an addendum to the assessment report. Fewer scenario analyses were done for FICE, because data were unavailable. Results of the scenario analyses show that NBI and i‑scan were dominant in all scenario analyses when compared with histopathology.

4.47 When FICE was compared with histopathology, it was cost effective in all scenario analyses. FICE was cheaper and more effective than histopathology and therefore was dominant when:

  • the risk-category distributions for the cohort were changed to reflect a population that was having surveillance colonoscopy

  • the risk-category distributions for the cohort were changed to reflect a cohort with symptoms and

  • the discard strategy was applied and diagnostic accuracy data were used for all levels of confidence for characterisations in the whole colon.

4.48 When alternative utility values were used from Farkkila et al. (2013), FICE was cheaper and slightly less effective compared with histopathology and had an ICER of £1,273,941 saved per QALY lost.

4.49 When diagnostic accuracy data were used from studies that reported data for endoscopists experienced in using NBI for the whole colon and the rectosigmoid colon, the results were similar to the base-case analyses for virtual chromoendoscopy and NBI dominated histopathology.

4.50 The effect of using virtual chromoendoscopy (NBI) for surveillance was explored and found to be small; it was estimated to increase cost savings by £20 and increase QALYs gained by 0.0003.

4.51 The EAG produced an addendum with 2 scenario analyses on adverse events. The first analysis varied the rate of perforation during colonoscopy using ratios from the data in Rutter et al. (2014), and found that cost savings for all 3 technologies decreased slightly in relative and absolute terms, and the QALYs decreased slightly in absolute terms, whereas the relative change was large (see table 5). NBI and i‑scan still dominated histopathology and the ICER for FICE increased to £126,229 saved per QALY lost. The second analysis included the risk of an adverse event happening during all colonoscopies, as well as for colonoscopies with polypectomy. This analysis also used data from Rutter et al. and found that cost savings for all 3 technologies decreased slightly in relative and absolute terms, and the QALYs decreased slightly in absolute terms, whereas the relative change was large (see table 6). NBI and i‑scan still dominated histopathology and the ICER for FICE increased to £342,438 saved per QALY lost.

Table 5 Cost-effectiveness results with the revised rate of perforation during colonoscopy using data from Rutter et al. (2014)

Base‑case inc cost

Revised inc cost

Relative change in cost compared with base case

Base-case inc QALYs

Revised inc QALYs

Relative change in QALYs compared with base case

Histopathology versus NBI

−£73.10

−£72.47

−0.9%

0.0005

0.0001

−80%

Histopathology versus FICE

−£87.70

−£86.92

−0.9%

−0.0001

−0.0007

−600%

Histopathology versus i‑scan

−£79.21

−£78.60

−0.8%

0.0007

0.0002

−71%

Abbreviations: FICE, flexible spectral imaging colour enhancement; Inc, incremental; NBI, Narrow Band Imaging; QALY, quality-adjusted life year.

Table 6 Cost-effectiveness results with risk of perforation and increased bleeding in all colonoscopies including those without polypectomy

Base‑case inc cost

Revised inc cost

Relative change in cost compared with base case

Base-case inc QALYs

Revised inc QALYs

Relative change in QALYs compared with base case

Histopathology versus NBI

−£73.10

−£73.06

−0.05%

0.0005

0.0004

−20%

Histopathology versus FICE

−£87.70

−£87.65

−0.06%

−0.0001

−0.0003

−200%

Histopathology versus i‑scan

−£79.21

−£79.16

−0.06%

0.0007

0.0006

−15%

Abbreviations: FICE, flexible spectral imaging colour enhancement; Inc, incremental; NBI, Narrow Band Imaging; QALY, quality-adjusted life year.

One-way deterministic sensitivity analyses results

4.52 The one-way deterministic sensitivity analyses found that the parameters with the most influence on the cost effectiveness of the tests were pathology cost, the probability of perforation with polypectomy, and the proportion of patients who die from perforation. All one-way sensitivity analyses showed that NBI, FICE and i‑scan were cost effective compared with histopathology at a maximum acceptable ICER of £30,000 per QALY gained.

Probabilistic sensitivity analysis results

4.53 The EAG did a probabilistic sensitivity analysis by varying the base-case inputs for the decision tree. The analysis was done by running the model 5,000 times. Each time it was run, the inputs were varied according to the distribution of the input.

4.54 The probabilistic sensitivity analysis found that i‑scan was more likely to be cost effective than NBI and FICE. At a maximum acceptable ICER of £20,000 per QALY gained, i‑scan was cost effective in 85.2% of the analyses, and at a maximum acceptable ICER of £30,000 per QALY gained i‑scan was cost effective in 99.5% of the analyses.

  • National Institute for Health and Care Excellence (NICE)