Cost-Effectiveness Analysis of Breast Cancer Control Interventions in Peru

Objectives: In Peru, a country with constrained health resources, breast cancer control is characterized by late stage treatment and poor survival. To support breast cancer control in Peru, this study aims to determine the cost-effectiveness of different breast cancer control interventions relevant for the Peruvian context. Methods: We performed a cost-effectiveness analysis (CEA) according to WHO-CHOICE guidelines, from a healthcare perspective. Different screening, early detection, palliative, and treatment interventions were evaluated using mathematical modeling. Effectiveness estimates were based on observational studies, modeling, and on information from Instituto Nacional de Enfermedades Neoplásicas (INEN). Resource utilizations and unit costs were based on estimates from INEN and observational studies. Cost-effectiveness estimates are in 2012 United States dollars (US$) per disability adjusted life year (DALY) averted. Results: The current breast cancer program in Peru ($8,426 per DALY averted) could be improved through implementing triennial or biennial screening strategies. These strategies seem the most cost-effective in Peru

Definition and classification of individual interventions (coverage) (based on [22]).

a<p>Endocrine therapy consists of 20 mg tamoxifen per day for 5 years.</p>b<p>Down-staging interventions cause a shift in stage distribution and are only modeled in combination with treatment of all stages (I–IV).</p>c<p>BAR was excluded as a standalone intervention in Costa Rica and Mexico.</p>d<p>Palliative care interventions are only applied to stage IV patients, and substitutes stage IV treatment.</p>e<p>The (neo)adjuvant chemotherapy combination regimen consists of 7 cycles of Epirubicin, Fluorouracil and cyclophosphamide (FEC regimen) Given on an outpatient basis.</p>f<p>Radiotherapy includes a standard dose of 50 Gy given in 25 fractions of 2 Gy on an outpatient basis.</p>g<p>Trastuzumab is given for 8 months.</p

Costa Rica - Results of sensitivity analysis on average cost-effectiveness ratio (ACER).

a<p>Alternative stage distribution: 9.4% stage I, 14.2% stage II, 58.0% stage III, 18.4% stage IV <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0095836#pone.0095836-Groot1" target="_blank">[7]</a>.</p>b<p>Alternative Case Fatality rates; 0,0174 stage I, 0,0284 stage II, 0,0832 stage III, 0,2855 stage IV <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0095836#pone.0095836-Ortiz1" target="_blank">[24]</a>.</p>c<p>Mechanical equipment (e.g. mammography machines, CT, X-ray).</p>d<p>Alternative assumptions on effectiveness of awareness interventions (−25%), sensitivity of CBE, and stage shifts of CBE screening.</p

Graphical representation of the model showing the relationships between the different health states through the incidence rates of breast cancer (Ix1–Ix4), the different stage specific case fatality rates (Fx1–4), and the background mortality (M) [7].

<p>Stage specific relapse rates to stage IV were used to correct health state valuations only (Rx1–Rx3).</p

Costa Rica - Average costs (US$), effects and cost-effectiveness of breast cancer control scenarios per year.

a<p>All costs in this table are in 2009 US$(1CRC = 0,001784 US$).</p>b<p>DALYs, disability-adjusted life-years (age weighted, discounted).</p>c<p>ACER: Average cost-effectiveness ratio compared to the do nothing-scenario (US$per DALY averted).</p>d<p>ICER: Incremental cost effectiveness ratio, ratio of additional cost per additional life-year saved when next intervention is added to a mix on the intervention path (additional US$ per additional DALY saved).</p

Analyzed interventions and the estimates used for the stage were interventions are applied to.

a<p>Case Fatality - Estimates for stages III and IV are from Groot et al. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0095836#pone.0095836-Groot1" target="_blank">[7]</a> and for stages I and II from Zelle et al. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0095836#pone.0095836-Zelle1" target="_blank">[22]</a>. The CFs for the untreated patients are from Groot et al. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0095836#pone.0095836-Groot1" target="_blank">[7]</a> and were corrected based on Bloom et al <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0095836#pone.0095836-Bloom1" target="_blank">[57]</a>.</p>b<p>Disability Weights - Estimates from Zelle et al.<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0095836#pone.0095836-Zelle1" target="_blank">[22]</a>.</p>c<p>Current stage distribution CR is based on Ortiz <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0095836#pone.0095836-Ortiz1" target="_blank">[24]</a>; MX onKnaul et al. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0095836#pone.0095836-Knaul2" target="_blank">[17]</a>; Effects of MAR derived from Devi <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0095836#pone.0095836-Devi1" target="_blank">[50]</a>; Effects of screening interventions were based on stage shifts from baseline Groot et al.<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0095836#pone.0095836-Groot1" target="_blank">[7]</a> to the stage distribution USA in Bland et al. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0095836#pone.0095836-Bland1" target="_blank">[58]</a>. Stage shifts were adapted by calculating relative differences in detection rates between the USA and CR/MX from Duffy & Gabe <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0095836#pone.0095836-Duffy1" target="_blank">[59]</a>. Calculations included age-specific incidence (MoH CR & Unidad Analysis Económica MX), prevalence (WHO 2008), sojourn time Duffy & Gabe <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0095836#pone.0095836-Duffy1" target="_blank">[59]</a>, sensitivity Bobo et al. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0095836#pone.0095836-Bobo1" target="_blank">[60]</a> and attendance rates (75% in the USA vs. 80% in Costa Rica and Mexico).</p>d<p>We assumed in Mexico implementing MAR could not lead to a higher proportion of stage IV patients and increase stage III with the difference of 0.6%.</p

Mexico- Results of sensitivity analysis on average cost-effectiveness ratio (ACER).

a<p>Unidad de Análisis Económico - 8.4% stage I, 38.5% stage II, 42.5% stage III, 10.6% stage IV <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0095836#pone.0095836-Comisin1" target="_blank">[42]</a>.</p>b<p>9.7% stage I, 52.7% stage II, 34.8% stage III, 2.8% stage IV <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0095836#pone.0095836-FloresLuna1" target="_blank">[41]</a>.</p>c<p>9.4% stage I, 14.2% stage II, 58.0% stage III, 18.4% stage IV <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0095836#pone.0095836-Groot1" target="_blank">[7]</a>.</p>d<p>Alternative Case Fatality rates: 0,013 stage I, 0,042 stage II, 0,102 stage III, 0,266 stage IV <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0095836#pone.0095836-Salomon1" target="_blank">[35]</a>.</p>e<p>Mechanical equipment (e.g. mammography machines, CT, X-ray).</p>f<p>Alternative assumptions on effectiveness of awareness interventions (−25%), sensitivity of CBE, and stage shifts of CBE screening.</p

Average utilization of diagnosis and treatment ingredients and unit costs per patient.

a<p>Based on estimates by Costa Rican CCSS.</p>b<p>Unit costs WHO-CHOICE database in 2000 US. Corrected for inflation: 2000–2009 (2.81 in CR & 1.66 in MX). 2009 exchange rates were used (560.45 CRC/US & 13.06 MXN/US$).</p>c<p>Based on values of IMSS.</p>d<p>Based on communication with Unidad de Análisis Económico of MoH.</p>e<p>Based on Norum et al. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0095836#pone.0095836-Norum1" target="_blank">[61]</a>.</p>f<p>Based on Knaul et al. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0095836#pone.0095836-Knaul1" target="_blank">[11]</a>.</p>g<p>palliative care (substitutes stage IV treatment).</p>h<p>50 Gy given in 25 fractions of 2 Gy.</p>i<p>daily dose of 20 mg. Tamoxifen for 5 years.</p>j<p>7 cycles of Epirubicin, Fluorouracil and cyclophosphamide (FEC regimen).</p>k<p>1 fraction of 10 Gy.</p>l<p>40 ml/54 s days.</p>m<p>35 mg/54 days.</p>n<p>8 mg/day.</p>o<p>751mg/day.</p>p<p>5 mg/day.</p

Cost-effectiveness analysis of breast cancer control interventions in peru

Contains fulltext : 125263.pdf (publisher's version ) (Open Access)OBJECTIVES: In Peru, a country with constrained health resources, breast cancer control is characterized by late stage treatment and poor survival. To support breast cancer control in Peru, this study aims to determine the cost-effectiveness of different breast cancer control interventions relevant for the Peruvian context. METHODS: We performed a cost-effectiveness analysis (CEA) according to WHO-CHOICE guidelines, from a healthcare perspective. Different screening, early detection, palliative, and treatment interventions were evaluated using mathematical modeling. Effectiveness estimates were based on observational studies, modeling, and on information from Instituto Nacional de Enfermedades Neoplasicas (INEN). Resource utilizations and unit costs were based on estimates from INEN and observational studies. Cost-effectiveness estimates are in 2012 United States dollars (US$) per disability adjusted life year (DALY) averted. RESULTS: The current breast cancer program in Peru ($8,426 per DALY averted) could be improved through implementing triennial or biennial screening strategies. These strategies seem the most cost-effective in Peru, particularly when mobile mammography is applied (from $4,125 per DALY averted), or when both CBE screening and mammography screening are combined (from$4,239 per DALY averted). Triennially, these interventions costs between $63 million and$72 million per year. Late stage treatment, trastuzumab therapy and annual screening strategies are the least cost-effective. CONCLUSIONS: Our analysis suggests that breast cancer control in Peru should be oriented towards early detection through combining fixed and mobile mammography screening (age 45-69) triennially. However, a phased introduction of triennial CBE screening (age 40-69) with upfront FNA in non-urban settings, and both CBE (age 40-49) and fixed mammography screening (age 50-69) in urban settings, seems a more feasible option and is also cost-effective. The implementation of this intervention is only meaningful if awareness raising, diagnostic, referral, treatment and basic palliative services are simultaneously improved, and if financial and organizational barriers to these services are reduced

Graphical representation of the model.

<p>Graphical representation of the model showing the relationships between the different health states through the incidence rates of breast cancer (Ix1–Ix4), the different stage specific case fatality rates (Fx1–4), and the background mortality (M). Stage specific relapse rates to stage IV were used to correct the disability weights (Rx1–Rx3).</p