Model overview

The study methods followed the Burden of Disease Epidemiology, Equity and Cost-Effectiveness Programme (BODE³) Protocol [19]. We adapted a previous Markov model on the cost-utility of girls-only HPV vaccination [20], to estimate quality-adjusted life years (QALYs) gained and net health system costs, for girls-only and girls and boys vaccination. The QALY metric captures both years of life lost from premature death, and loss of quality of life through morbidity. To value this health loss, we used disability weights (DWs), as outlined below. We formally use the term QALY^DW in this paper’s Methods and Results, but shorten it to QALY in other sections.

The two main adaptations were adding vaccine and administrative costs per vaccinated boy, and additional reductions in HPV infection due to additionally vaccinating boys.

Health system costs included both direct intervention costs and downstream health system costs incurred/averted. A 3% discount rate applied to costs and quality-adjusted life years (QALYs^DW) gained. Currency conversions were conducted using the OECD purchasing power parity (PPP) estimates, to eliminate the differences in price levels between countries [21]. In 2011, the PPP values were US$1 = NZ$1.48.

HPV vaccination was modeled as preventing CIN I-III, cervical, anal, oropharyngeal and vulval cancers and anogenital warts (Figure 1) using rates of all-cause mortality, excess mortality rates from cancer [22], and incidence rates for cancer [23] and morbidity states [24]. Vaginal and penile cancers were excluded due to their small contribution to the HPV16/18-related cancer burden (<3%). Recurrent respiratory papillomatosis (RRP) was excluded due to sparse data. Cervical cancer screening programs were assumed to continue in New Zealand, but these costs were excluded from our analyses.

Model input parameters

Morbidity

Disability weights (DWs) for each disease state were used, with uncertainty, on a scale from 0 (full health) to 1.0 (death) (Additional file 1: Table S1). Expected population morbidity (i.e., due to disease other than HPV-related disease) was allowed for by using the average ethnic and age-specific prevalent years of life lived in disability from the New Zealand Burden of Disease Study [19], limiting the maximum QALYs^DW gained with increasing age. Consider a non-Māori male aged 50–54 with oropharyngeal cancer in the remission phase (expected DW = 0.248, although actually modeled with uncertainty), with an expected background morbidity of 0.112 [19]; his expected QALYs^DW awarded in that year would be (1–0.248) × (1–0.112) = 0.668.

Incidence and survival

Cancer incidence rates were those predicted for 2011 with trends projected into the future based on regressions on New Zealand Cancer Registry data [25]. Therefore, when the model was run without intervention effects, the model produced the same disease data as the input dataset. Incidence rates for other diseases and the proportion of disease due to HPV 16/18 or 6/11 were compiled from various sources, including national cancer registration data [24] and screening program information [26]. Australian burden of disease models were used to allocate durations for each cancer in diagnosis and treatment, remission, pre-terminal and terminal states, with attendant DWs sourced from the Global Burden of Disease 2010 [27] with modification to the New Zealand distribution of cancers [19]. Cancer survivors were modeled in the cancer state for five cycles accumulating QALYs with morbidity adjustment via the DWs, then returned to the healthy state.

Health system cost parameters

Just as QALYs^DW were awarded to each individual as they traveled through states, so were health system costs. We used routine, linked administrative health data for the entire New Zealand population with costs attached, as described elsewhere [19]. We assigned health system costs by sex and age to the healthy state (see Additional file 1: Table S2). The added cost for cancer patients at different stages of care (i.e., diagnosis, remission, terminal) were estimated using gamma regression, as per the previous research in the BODE³ Program for girls-only vaccination [20]. The added cost for other disease states (CIN I-III and warts) were simple averages. All health system costs were measured in 2011 New Zealand dollars.

Interventions

Intervention costs

The vaccination costs were calculated per fully vaccinated girl/boy, based on the annual vaccine cost paid by the Ministry of Health (in 2011), resulting in the vaccine cost per dose of NZ$113 (Table 1). The delivery/administration costs of three main interventions were NZ$141 or NZ$126 per dose depending on the method of delivery (i.e., in schools and primary care settings or in schools only). These costing data were based on official Ministry of Health data which include funding to cover program management (a component which is often omitted from ‘administration costs’ of other studies). The vaccination costs were multiplied by three doses, and then assigned for each fully vaccinated member of the cohort (allowing for vaccine coverage); incomplete vaccine courses were not considered. We used a discount rate of 3% and as for health system costs, all intervention costs were measured in 2011 New Zealand dollars.

In scenario analyses, we explored reductions in vaccine cost-per-dose at several levels of reduction down to $1 and lower administrative costs (NZ$19 per dose). We also conducted a scenario analysis which removed the herd immunity cancer reduction benefits for males in the girls-only vaccination program (1G). We compared these results with the benefits of adding boys to the vaccination program (1G + B) and included MSM-attributable warts and cancers in the disease incidence data that populates the model. We also performed a threshold analysis to estimate the maximum cost per delivered vaccine dose (including vaccine and administration costs) which would allow vaccination of boys in addition to girls to be cost-effective compared to girls only vaccination.

Considering uncertainty and performing cost-effectiveness analysis

Monte Carlo simulation was used, with 2,000 draws from input parameter distributions. Incremental QALYs^DW, costs and incremental cost-effectiveness ratios (ICERs) were calculated for each draw of Monte Carlo simulation. All modeling and uncertainty analyses were undertaken in TreeAge Pro 2012. ICERs were calculated for each intervention including boys (1G + B and 2G + B), compared to the equivalent intervention for girls-only (1G and 2G) and compared to no vaccination program. In line with contextualizing ICER results with GDP per capita comparisons [34], we made such comparisons for the New Zealand setting. Because there is no universally accepted threshold in New Zealand for describing interventions as being “cost-effective” or not, we relied on the WHO definition and used a nominal GDP per capita of NZ$45,000 in 2011 (US$29,600) as being such a threshold. Using the GDP per capita level is based on the WHO description of interventions below this value as being ‘very cost-effective’ (for the WPROA Region to which New Zealand belongs [34]).

Discussion of main findings and interpretation

Our finding that HPV vaccination of boys was not cost-effective when vaccination coverage in a girls-only program was high (>50%) was consistent with other modeling on the incremental cost-effectiveness of adding boys to girls-only vaccination programs [1, 35]. Specifically, we found that providing vaccination of boys at the current coverage level for girls would cost US$61,400 per QALY gained (NZ$118,000, 95% UI: $57,100 to $215,000) compared to the current girls-only program. For comparison to other international studies, it is useful to use US dollars. In the base case, we assumed the current New Zealand vaccine cost of US$59 (NZ$113) per dose and administrative costs of US$73 (NZ$141) per dose. By comparison, US models (which do not generally assume vaccine is delivered as a publicly-funded health service) assumed vaccine costs (in 2011 USD) of US$101-135 per dose [35, 36] and US$61 administration costs per dose [35]. Those same studies, when comparing the addition of boys to girls-only vaccination programs, and including all HPV-related diseases and similar vaccine efficacy and duration to our study, were found to be more cost-effective than our study, ranging from US$26,000 [36] to $41,000 [35] per QALY for coverages under 50% and $62,000/QALY for coverages up to 70% [37]. While direct comparisons between cost-effectiveness analyses are difficult, the observed differences in cost-effectiveness are most likely due to varying disutility assigned to genital warts and CIN states (less in our model than in the US studies, see Additional file 1: Table S1; and uncertainty analyses in our parallel girls-only vaccination paper demonstrated that disutility assigned to these states was a major driver of uncertainty in the final ICER [20]). Also, the inclusion of future health system costs in our model will slightly lessen cost-effectiveness (scenario analyses about excluding unrelated health system costs show little impact, see Table 4) and our use of a cohort (rather than a population-wide) model may have influence. Our study also found that vaccination of boys only became cost-effective under the conditions of both an extremely low vaccine price (NZ$1 per dose) and with very low administration costs (NZ$19 per dose), up to a maximum total cost of NZ$125 per dose delivered. However, even at a lower cost per dose delivered, because a more intensive female-only program is equally effective and less costly than adding boys to the current program, increasing coverage in girls would generally remain a preferable strategy if this could be achieved.

Study strengths and limitations

A strength of this study is its potential to fill a gap in the knowledge base for New Zealand policy makers who may be considering what next after the relatively successful implementation of a girls-only HPV program. More broadly it adds to the relatively small number of studies that have addressed the cost-effectiveness of vaccinating boys in a publicly funded system.

Nevertheless, a limitation is the lack of local data to build a dynamic HPV infection model and thus, our reliance on HPV reduction results from a Canadian dynamic model. Thus we implicitly assumed that sexual behavior in New Zealand and Canada are broadly similar for reasons outlined in the Methods section. This should not be overly problematic if vaccine coverage rates are not correlated with level of sexual behavior or factors which influence choice of sexual partner [38]. Furthermore, refined and improved HPV modeling specific to New Zealand would probably not alter our conclusion that vaccination of boys is not cost-effective using a NZ$45,000 per QALY threshold (see Additional file 1: Figure S1). Rather, a reduction in vaccine cost – perhaps plausible in the future – is more likely to influence whether vaccination of boys is cost-effective in New Zealand (see Table 4 and Additional file 1: Figure S1). That is, uncertainty in applying Brisson et al. outputs (based on their model assumptions, Canadian sexual contact patterns, etc.) to the New Zealand situation – whilst important – does not appear to be enough to alter the general conclusion that vaccinating boys in New Zealand is not cost-effective (in the absence of large vaccination price reductions). Another related issue was our use of a ‘steady state’ of HPV reduction in our population model. Our model estimates likely health impacts, costs and cost-effectiveness for cohorts of 12-year-olds one to three decades into the future after the first cohort is vaccinated. This is a robust baseline model for the following reasons. First even for the first cohort vaccinated, they will still receive the benefits of direct immunity (i.e., the majority of the benefit from HPV 16/18 reduction, as herd effects are smaller for these HPV types, and also much of benefit from HPV 6/11 reduction, which has greater herd immunity [13]). The first cohort vaccinated will also receive the benefit of herd immunity from vaccination of the cohort’s immediate age contemporaries and subsequent vaccination of younger cohorts and additionally some herd immunity from older cohorts included in the catch-up program. Girls up to nine years older than the modeled cohort (i.e., born in 1990 or later) were offered vaccination, with achieved three-dose coverage in the range 37-54% [39]. Last, there is a ‘lead time’ benefit. For example, those vaccinated at age 12 years likely have a modal age of coitarche of 15–18 years [30], and a period of maximum exposure to HPV, due to multiple sexual partners, from age 15 to 30 years. This cohort will start to benefit from herd immunity as previous modeling studies e.g., [15] and now observed data from several countries [40] suggest that HPV prevalence is likely to drop rapidly after the introduction of HPV vaccination.

We did not include any costs associated with starting-up a boys’ vaccination program, as these would likely be comparatively small when considered over the longer term and because including boys is extending the existing girls-only program, rather than a new program. (Scenario analyses available from the authors on request confirm this). We also did not model different coverage rates for boys and girls, given we expected minimal differences can be achieved, particularly with school-based vaccination programs. We did not include the health benefits of cross-protection of the quadrivalent vaccine against other HPV strains which cause disease; such analyses would likely have only a minor positive impact on QALYs gained and therefore only modestly affect cost-effectiveness [41]. Our modeling does not separately model MSM, although we did conduct a scenario analysis which removed the herd immunity cancer reduction benefits for males in the girls-only vaccination program (1G). We compared these results with the benefits of adding boys to the vaccination program (1G + B) and included MSM-attributable warts and cancers in the disease incidence data that populates the model. Should a targeted program be able to successfully deliver vaccination to MSM at a young age (e.g., in primary care settings), it seems highly likely that this would be cost-effective [17].

Our costing data for vaccination delivery were based on official Ministry of Health data which include funding to cover program management (a component which does not seem to typically be included in the ‘administration costs’ of other studies). We recognize that this cost and relatively high vaccine costs do not account for future plausible developments (e.g., in changes in delivery (see below) or declines in vaccine prices). The latter is particularly relevant to New Zealand, which has a single government-owned agency (Pharmac) that purchases pharmaceuticals for the whole country and has recently taken over national-level vaccine purchases (from the Ministry of Health). This development could result in substantial reductions in vaccine prices in future purchase arrangements.

Research implications

The cost-effectiveness results were sensitive to vaccine and administration costs, suggesting an analysis of a vaccination program with only two required doses would be useful in future research. However, if the efficacy of two doses were similar to that of three doses, vaccination of boys would still not be cost-effective based on our findings from our ‘best’ model (i.e., that with current prices), unless the total cost per vaccinated individual was less than NZ$375 (based on our threshold analysis). For example, for incremental comparison B in Table 2 (1G + B c.f.1G) the cost of the intervention (first row) would decrease by a third or $3610, and the net incremental cost would therefore reduce by 40% from $8,996 to $5390. Hence the ICER would also reduce by 40% to about $70,400 per QALY gained.

If new evidence of lower vaccine bulk prices tendered by developed countries becomes available, future modeling may be worthwhile as it is likely to suggest improvements in cost-effectiveness (lower ICERs). Nevertheless, from our analyses, the vaccine price would have to be substantially less than the NZ$113 per dose assumed here to include boys in any vaccination program, and the overall costs of delivering a dose would have to be less than NZ$125, or less than an overall cost per vaccinated individual of NZ$375. Countries with other school-based vaccination programs (e.g., the DTP booster given to 11-year-olds as per the New Zealand schedule) could also explore the administrative cost savings by providing dual vaccination at this one service. Such combinations of ‘piggy-backing’ of administration cost reductions along with reductions in vaccine price appear, in our modeling, to be the major way that vaccination of boys could start to become cost-effective in the current New Zealand setting.

Possible policy implications

Given the findings of this modeling, policy makers in settings like New Zealand (with relatively low HPV coverage for girls) should probably focus more on improving HPV vaccination for girls than adding HPV vaccination for boys. Indeed, they should probably set decision review dates around HPV vaccination for boys out into the medium term or at least until vaccine prices drop substantially.

If policy makers are under public pressure to provide vaccination for boys then they should ideally focus on ways to reduce the overall cost per vaccinated individual, as this will increase the cost-effectiveness of adding boys to the program, for example via research around cost-reduction measures (e.g., how to reduce delivery costs and also how to obtain lower cost vaccine as detailed in the section above). They could also reassure the public that the initial most logical goal of achieving higher HPV vaccination coverage for girls will actually produce substantial spillover benefits via herd immunity for boys.