Result card

  • ECO5: What is the incremental cost-effectiveness ratio (FIT versus gFOBT; FIT versus no screening; gFOBT versus no screening)?
English

What is the incremental cost-effectiveness ratio (FIT versus gFOBT; FIT versus no screening; gFOBT versus no screening)?

Authors: Principal Investigators: Anna-Theresa Renner, Ingrid Rosian-Schikuta, Investigators: Nika Berlic, Neill Booth, Valentina Prevolnik Rupel

Internal reviewers: Pseudo178 Pseudo178, Pseudo283 Pseudo283, Pseudo291 Pseudo291, Pseudo293 Pseudo293, Pseudo294 Pseudo294, Pseudo297 Pseudo297, Pseudo298 Pseudo298

The incremental cost-effectiveness ratio (ICER) of FIT versus gFOBT is based on the studies identified through the systematic literature search described above. In most of these studies the incremental cost-effectiveness ratio (ICER) was already calculated and explicitly given. For the remaining studies the incremental costs and effects of FIT versus gFOBT was calculated and divided to obtain the ICER:

ICER= DCosts/D Effects

For the estimation of the overall costs of the different screening technologies most of the cost-effectiveness models adopted a payer’s perspective and hence only included the direct costs of the screening programme, the follow-up tests and the treatment of a detected adenoma or cancer. Heitman et al. (2009 and 2010) {14, 15} also added indirect costs of the patient time and of the transport. 

The 16 identified studies all contained an estimation of either cost-effectiveness (effects are measured in life-years gained) {10, 12, 13, 16-19, 25} or cost-utility (effects are measured in QALYs) {14, 15, 20-24}, based on health-economic models.

The calculated ICERs varied across the studies as was expected due to the different modelling structures and parameter assumptions. However, given that the studies were undertaken in different settings (countries and health-care systems) and used data from different points in time the result that FIT was estimated to be ‘dominant’ or have a relatively low incremental cost-effectiveness ratio (ICER), is consistent across almost all the studies.

The consequences of screening for colorectal cancer can potentially occur throughout the participants’ remaining lifetime. Hence, the time horizon for a study modelling the costs and effects of different screening strategies for CRC should be over a lifetime, if sufficient information is available to support such an approach. If a life-time horizon is not taken or not possible, then there is a potential that important costs and/or effects will be ignored. For the reason being that costs of a screening occur immediately, whereas the effects (life years / QALYs gained) usually occur later in life, a shorter time horizon might underestimate the cost-effectiveness of a technology. There are three studies included in this review that use shorter than lifetime time horizons (10 {19}, 20 {11, 12, 17} and 30 years {16, 24}).

Costs per life-year gained when using FIT instead of gFOBT:

In one third of the reported ICERs (four of 12) FIT dominates gFOBT, meaning that FIT is associated with lower costs and higher effects than gFOBT (see table below). However, most of these studies were based on US-data {10, 18}. One model estimated that FIT was dominated by gFOBT if used in a screening population of 50-80-year-olds {25}; this is the study were Hemeoccult SENSA was used, which is assumed to have effects similar to those of FIT, and to cost less than FIT. The remaining estimates of the ICER are ranging between around 3,000 € and 17,500 € per life-year gained {10, 12, 13, 16, 17, 25}. The publication date of the studies does not seem to play a significant role in the differences between the ICERs.

Table 7: Incremental Cost Effectiveness Ratios (ICERs) using life years gained

Author (year)

 

ICER[1]

(=ΔCosts/ Δlife-year gained)

Comparators

Screening age

Costs included

Discount rate

Country

van Ballegooijen et al. (2003) {10}

FIT dominates gFOBT

FIT 98% specificity vs. gFOBT (Hemoccult II and Hemoccult Sensa); annual

56-79

 

Direct costs derived from Medicare fee schedule including co-payments born by the patient (in 2002 US Dollars)

 

3%

USA

FIT dominates gFOBT

FIT 95% specificity vs. gFOBT (Hemoccult Sensa); annual

6,400 US$ per LYG

(~ 4,700 €)

FIT 95% specificity vs. gFOBT (Hemoccult II)

Berchi et al. (2004) {12}

3,000€ per LYG

FIT vs. gFOBT; after 20 years; biennial

50-74

Direct costs based on French health care insurance contracts (in 2003(b) Euros)

5%

France

Hassan et al. (2011) {13}

8,600 € per LYG

FIT vs. gFOBT; biennial

50-74

Direct costs based on French health care insurance contracts (in 2010(b) Euros)

3%

France

17,600 € per LYG

Annual FIT vs. biennial gFOBT

Heresbach et al. (2010) {16}

5,500 € per LYG

FIT vs. gFOBT; after 30 years; biennial

50-74

Direct costs obtained from French health care system (in 2005/07(a) Euros)

3%

France

Lejeune et al. (2010) {17}

3,000 € per LYG

FIT vs. gFOBT; after 20 years; biennial

50-74

Direct costs based on French health care insurance contracts (in 2006 Euros)

3%

France

Parekh et al. (2008) {18}

FIT dominates gFOBT

FIT vs. gFOBT; annual;

50-80

Direct costs derived from Medicare fee schedule (in 2006 US Dollars)

3%

USA

van Rossum et al. (2011) {19}

FIT dominates gFOBT

FIT vs. gFOBT; after 10 years; 1 round of screening

50-75

Direct costs based on Dutch health care charges and retail prices (in 2009(a) Euros)

3%

Netherlands

Zauber (2010) {25}

 

22,100 US$ per LYG

(~ 16,400 € )

FIT vs. gFOBT (Hemoccult II)

50-80

 

Direct costs derived from Medicare fee schedule excluding co-payments borne by the patient (in 2007 US Dollars)

3%

USA

FIT is dominated by gFOBT

FIT vs. gFOBT (Hemoccult SENSA); annual

 

  1. year of price based on referenced literature
  2. year of price not given, and assumed to correspond to year prior to publication

 

Costs per QALY gained when using FIT instead of gFOBT:

All of the studies that used QALYs as a measure of effectiveness were conducted recently, i.e., between 2009 {14} and 2012 {20} (see table below).

Half of the estimated ICERs based on the included models show that FIT dominates gFOBT {14, 15, 23, 24}. The settings (Canada, England and the Netherlands), the screening age (50-74, 60-74 and 45-80) and the assumed base-case discount rates (3%, 3.5% and 5%) vary across these studies. Two of the ICERs where FIT dominated gFOBT were estimated from a model that included costs for patient time and transport to the screening {14}. The ICERs of the remaining four studies {14, 20-22} range between around 400 € and almost 9,000 € per QALY which is well below one often-suggested ICER threshold of 50,000 US $ (around 36,960 €).

Table 7: Incremental Cost Effectiveness Ratios (ICERs) using QALYs

Author (year)

ICER (1)

(= ΔCosts/ ΔQALY gained)

Comparators

Screening age

Costs-included

Discount rate

Country

Heitman et al. (2009) (2) {14}

FIT dominates gFOBT

FIT-low vs. gFOBT; annual

50-74

Direct costs derived from the Canadian health care system, costs of patient time and transport costs (in 2007 CAN Dollars)

5%

Canada

FIT dominates gFOBT

FIT-mid vs. gFOBT; annual

5,000 CAN$ per QALY (~ 3,600 €)

FIThigh vs. gFOBT; annual

Heitman et al. (2010) {15}

FIT dominates gFOBT

FIT-mid, -low and -high vs. gFOBT low and high

 

50-75

Direct costs derived from the Canadian health care system, costs of patient time and transport costs (in 2007 CAN Dollars)

5%

Canada

Sharp et al. (2012) {20}

400 € per QALY

FIT vs. gFOBT; biennial;

55-74

Direct costs based on Health Service Executive (in 2008 Euros)

4%

Ireland

Sobhani et al. (2011) {21}

8,800 € per QALY

FIT vs. gFOBT; biennial

50-75

Direct costs based on literature (in 2010 Euros)

3%

France

Telford et al. (2010) {22}

600 CAN$ per QALY (~ 400 €)

FIT vs. gFOBT; annual

50-75

Direct costs based on data from the Provicial Ministry of Health (in 2007 CAN Dollars)

5%

Canada

Whyte et al. (2012) {23}

FIT dominates gFOBT

FIT vs. gFOBT; biennial;

60-74

Direct costs based on data from the National Health Service

3.5%

England

Wilschut et al. (2011) {24}

FIT dominates gFOBT

FIT (at all cut-off levels) vs. gFOBT; after 30 years; annual

45-80

Direct costs derived from the Dutch health care system (in 2010(a) Euros)

3%

Netherlands

  1. year of price not given, and assumed to correspond to year prior to publication

 

(1) Numbers are rounded to full hundreds (exact estimates can be found in the Appendix “Study Designs and Results”

(2) The time horizon is not clearly stated in the published article but it seems likely to be over a lifetime.

 

[1] Numbers are rounded to full hundreds (exact estimates can be found in the Appendix “Study Designs and Results”

Adjustment of price levels:

 

The results of the cost-effectiveness models were not adjusted to one price level or one point in time. Since most studies (12 of 16) were conducted in or after 2008 this might cause non-significant changes to the ranking of the ICERs in the tables but is unlikely to change the overall order dramatically.

 

Sensitivity analyses:

An analysis of the robustness of the results was not given by all studies, especially not on the gFOBT-vs.-FIT ICER since the primary aim of some studies was to compare not only FIT and gFOBT but also other screening strategies, or no screening at all.

 

  1. Studies life years gained as the outcome measure:

 

The result of the study of van Ballegooijen et al. (2003) revealed that FIT with a 98% specificity dominates gFBOT (Hemeoccult II) and that this holds even if the compliance rate decreases from 100% to 60% for gFOBT and 90% for FIT {10}.

In a Monte Carlo simulation Parekh et al. (2008) shows that FIT dominates a no screening strategy in 100% of the simulations whereas gFOBT dominates a no-screening strategy in only around 95% of the simulations {18}. A direct comparison of FIT and gFOBT using a Monte Carlo simulation was not conducted.

Van Rossum et al. (2011) present the results of a deterministic sensitivity analysis, with the result that only very low CRC incidence and very high estimated costs of colonoscopy have a negative impact on the cost-effectiveness of FIT {19}.

Another deterministic sensitivity analysis was conducted by Berchi et al. (2004) using different assumptions about the participation rate, the costs of gFOBT, costs of colonoscopy, costs of CRC treatment, quality of FIT and natural history of disease {12}. The results suggest a robustness of the finding that FIT is more effective but also more costly than gFOBT.

Lejeune et al.’s (2010) sensitivity analysis also shows that FIT remained more effective and more costly for all parameter variations, but that the ICER increases if the price for gFOBT is decreased by 50% or if the sensitivity of FIT decreases. The ICER decreases if the price for FIT decreases by 50%, if the participation rate of FIT is increased by 10%, if the lead time associated with FIT increases or if FIT`s sensitivity increases {17}.

A probabilistic sensitivity analysis of the model designed by Heresbach et al. (2010) shows that FIT is more effective than gFOBT in 97.8% and dominant in 8.9% of the simulations {16}.

Hassan et al. (2011) also conducted a probabilistic sensitivity analysis with the result that annual FIT had the highest net-benefit in 20% of the simulations, compared to other strategies such as sigmoidoscopy every five years, of colonoscopy every 10 years which had the highest net-benefit in 40% and 26% of the simulations respectively {13}.

In the publication of Zauber (2010) no sensitivity analysis is reported {25}.

 

  1. Studies using QALYs gained as the outcome measure:

 

The univariate sensitivity analysis of Heitman et al. (2009) showed that changing the costs or the screening interval (biennial instead of annual) did not change the dominance of FIT-mid (representing studies with “mid-range” test performance) over gFOBT {14}.

In the study published by Heitman et al. one year later (2010) no sensitivity analysis of the direct comparison of FIT versus gFOBT was published, but the probabilistic analysis shows that in nearly 100% of the simulations FITmid was cost saving and more effective compared to no screening, but no direct comparison of {15}.

The results of the model presented by Whyte et al (2012) are highly sensitive to several model parameters such as uptake, endoscopy costs and FIT thresholds. In the probabilistic sensitivity analysis FIT remains cost-effective compared to gFOBT at an assumed willingness-to-pay threshold of 20,000 £ {23}.

Wilschut et al. (2011) conducted a deterministic sensitivity analysis on different parameters. FIT (50ng/ml) for the age group 45-80 years remained most cost-effective when attendance rate increased to 100%, quality of life loss was taken into account, fatal complications decreased, FOBT costs and colonoscopy costs were halved, and when complication and treatment costs were halved or doubled. FIT (50ng/ml) for the age group 50-80 years became more cost-effective for all other parameter changes {24}.

In the one-way sensitivity analysis of Sharp et al. (2012) the most influential parameters were the discount rate, the costs of the tests and the costs of managing CRC. The ICERs for FIT and gFOBT compared to no screening always remained below the chosen notional cost-effectiveness threshold (45,000 € per QALY). The probabilistic sensitivity analysis showed that uncertainty was greatest for FIT, but all cost-effectiveness ratios remained below the notional threshold and the incremental QALY gains for FIT exceeded those for gFOBT in most simulations {20}.

The model of Telford et al. (2010) was sensitive to variations in the sensitivity of the tests to detect advanced adenoma, the costs of the test, the compliance with screening and the costs of cancer care. The probabilistic sensitivity showed that the ranking of strategies did not change and that no strategy was dominant {22}.

In the model of Sobhani et al. (2011) the participation rate seems to have a very high impact on the results, whereas changing the compliance rate for colonoscopy did not change the results much. Throughout the one-way sensitivity analyses the 3-sample FIT with a cut-off level of 50ng/ml was consistently the most cost-effective choice {21}.

 

It is difficult to provide an overall statement on the robustness of the ICER estimations because neither the methods of sensitivity analysis nor the reporting of the results are standardised. The matter is further complicated by that fact that in some of the studies FIT is not directly compared to gFOBT but both are compared to no screening. As a consequence, the sensitivity analyses focus on the robustness of the cost-effectiveness compared to no screening.

 

In conclusion, the deterministic sensitivity analyses of the studies using life years gained as the outcome measure show that the model results are quite robust, especially to changes in compliance and participation rate, but might be sensitive to other assumptions, such as that the CRC incidence is very low, the costs of a colonoscopy or a gFOBT is very high or that the sensitivity of FIT decreases. The probabilistic sensitivity analyses suggest that the results are rather robust.

The sensitivity analyses of the studies using QALYs gained as the outcome measure show no common pattern and therefore no qualified statement about influential parameters can be given.

 

Six studies reported the result of a deterministic sensitivity analysis {10, 12, 17, 19, 21, 24}, four used a probabilistic method {13, 15, 16, 18}and four studies used both, a deterministic and a probabilistic analysis {14, 20, 22, 23}. Only one study did not report a sensitivity analysis {25}. 

Critical
Partially
Renner P et al. Result Card ECO5 In: Renner P et al. Costs and economic evaluation In: Jefferson T, Cerbo M, Vicari N [eds.]. Fecal Immunochemical Test (FIT ) versus guaiac-based fecal occult blood test (FOBT) for colorectal cancer screening [Core HTA], Agenas - Agenzia nazionale per i servizi sanitari regionali; 2014. [cited 16 June 2021]. Available from: http://corehta.info/ViewCover.aspx?id=206

References