Treat All versus targeted strategies to select HBV-infected people for antiviral therapy in The Gambia, west Africa: a cost-effectiveness analysis.

BACKGROUND: Global elimination of hepatitis B virus (HBV) requires expanded uptake of antiviral therapy, potentially by simplifying testing algorithms, especially in resource-limited countries. We evaluated the effectiveness, cost-effectiveness, and budget impact of three strategies that determine eligibility for anti-HBV treatment, as compared with the WHO 2015 treatment eligibility criteria, in The Gambia. METHODS: We developed a microsimulation model of natural history using data from the Prevention of Liver Fibrosis and Cancer in Africa programme (known as PROLIFICA) in The Gambia, for an HBV-infected cohort of individuals aged 20 years. The algorithms included in the model were a conventional strategy using the European Association for the Study of the Liver (EASL) 2017 criteria, a simplified algorithm using hepatitis B e antigen and alanine aminotransferase (the Treatment Eligibility in Africa for the Hepatitis B Virus [TREAT-B] score), a Treat All approach for all HBV-infected individuals, and the WHO 2015 criteria. Outcomes to measure effectiveness were disability-adjusted life years (DALYs) and years of life saved (YLS), which were used to calculate incremental cost-effectiveness ratios (ICERs) with the WHO 2015 criteria as the base-case scenario. Costs were assessed from a modified social perspective. A budget impact analysis was also done. We tested the robustness of results with a range of sensitiviy analyses including probabilistic sensitivity analysis. FINDINGS: Compared with the WHO criteria, TREAT-B resulted in 4877 DALYs averted and Treat All resulted in 9352 DALYs averted, whereas the EASL criteria led to an excess of 795 DALYs. TREAT-B was cost-saving, whereas the ICER for Treat All (US$2149 per DALY averted) was higher than the cost-effectiveness threshold for The Gambia (0·5 times the country's gross domestic product per capita: $352). These patterns did not change when YLS was the outcome. In a modelled cohort of 5000 adults (aged 20 years) with chronic HBV infection from The Gambia, the 5-year budget impact was $1·14 million for Treat All, $0·66 million for TREAT-B, $1·03 million for the WHO criteria, and $1·16 million for the EASL criteria. Probabilistic sensitivity analysis indicated that among the Treat All, EASL, and TREAT-B algorithms, Treat All would become the most preferred strategy only with a willingness-to-pay threshold exceeding approximately $72 000 per DALY averted or $110 000 per YLS. INTERPRETATION: Although the Treat All strategy might be the most effective, it is unlikely to be cost-effective in The Gambia. A simplified strategy such as TREAT-B might be a cost-saving alternative. FUNDING: UK Research and Innovation (Medical Research Council). TRANSLATION: For the French translation of the abstract see Supplementary Materials section.

Excess mortality associated with elevated body weight in the USA by state and demographic subgroup: A modelling study.

Background: The obesity epidemic in the USA continues to grow nationwide. Although excess weight-related mortality has been studied in general, less is known about how it varies by demographic subgroup within the USA. In this study we estimated excess mortality associated with elevated body weight nationally and by state and subgroup. Methods: We developed a nationally-representative microsimulation (individual-level) model of US adults between 1999 and 2016, based on risk factor data from 6,002,012 Behavioral Risk Factor Surveillance System respondents. Prior probability distributions for hazard ratios relating body-mass index (BMI) to mortality were informed by a global pooling dataset. Individual-level mortality risks were modelled accounting for demographics, smoking history, and BMI adjusted for self-report bias. We calibrated the model to empirical all-cause mortality rates from CDC WONDER by state and subgroup, and assessed the predictive accuracy of the model using a random sample of data withheld from model fitting. We simulated counterfactual scenarios to estimate excess mortality attributable to different levels of excess weight and smoking history. Findings: We estimated that excess weight was responsible for more than 1300 excess deaths per day (nearly 500,000 per year) and a loss in life expectancy of nearly 2·4 years in 2016, contributing to higher excess mortality than smoking. Relative excess mortality rates were nearly twice as high for women compared to men in 2016 (21·9% vs 13·9%), and were higher for Black non-Hispanic adults. By state, overall excess weight-related life expectancy loss ranged from 1·75 years (95% UI 1·57-1·94) in Colorado to 3·18 years (95% UI 2·86-3·51) in Mississippi. Interpretation: Excess weight has substantial impacts on mortality in the USA, with large disparities by state and subgroup. Premature mortality will likely increase as obesity continues to rise. Funding: The JPB Foundation, NIH, CDC.

Estimating the impact of the COVID-19 pandemic on diagnosis and survival of five cancers in Chile from 2020 to 2030: a simulation-based analysis.

BACKGROUND: The COVID-19 pandemic has strained health system capacity worldwide due to a surge of hospital admissions, while mitigation measures have simultaneously reduced patients' access to health care, affecting the diagnosis and treatment of other diseases such as cancer. We estimated the impact of delayed diagnosis on cancer outcomes in Chile using a novel modelling approach to inform policies and planning to mitigate the forthcoming cancer-related health impacts of the pandemic in Chile. METHODS: We developed a microsimulation model of five cancers in Chile (breast, cervix, colorectal, prostate, and stomach) for which reliable data were available, which simulates cancer incidence and progression in a nationally representative virtual population, as well as stage-specific cancer detection and survival probabilities. We calibrated the model to empirical data on monthly detected cases, as well as stage at diagnosis and 5-year net survival. We accounted for the impact of COVID-19 on excess mortality and cancer detection by month during the pandemic, and projected diagnosed cancer cases and outcomes of stage at diagnosis and survival up to 2030. For comparison, we simulated a no COVID-19 scenario in which the impacts of COVID-19 on excess mortality and cancer detection were removed. FINDINGS: Our modelling showed a sharp decrease in the number of diagnosed cancer cases during the COVID-19 pandemic, with a large projected short-term increase in future diagnosed cases. Due to the projected backlog in diagnosis, we estimated that in 2021 there will be an extra 3198 cases (95% uncertainty interval [UI] 1356-5017) diagnosed among the five modelled cancers, an increase of nearly 14% compared with the no COVID-19 scenario, falling to a projected 10% increase in 2022 with 2674 extra cases (1318-4032) diagnosed. As a result of delayed diagnosis, we found a worse stage distribution for detected cancers in 2020-22, which is estimated to lead to 3542 excess cancer deaths (95% UI 2236-4816) in 2022-30, compared with the no COVID-19 scenario, among the five modelled cancers, most of which (3299 deaths, 2151-4431) are projected to occur before 2025. INTERPRETATION: In addition to a large projected surge in diagnosed cancer cases, we found that delays in diagnosis will result in worse cancer stage at presentation, leading to worse survival outcomes. These findings can help to inform surge capacity planning and highlight the importance of ensuring appropriate health system capacity levels to detect and care for the increased cancer cases in the coming years, while maintaining the timeliness and quality of cancer care. Potential delays in treatment and adverse impacts on quality of care, which were not considered in this model, are likely to contribute to even more excess deaths from cancer than projected. FUNDING: Harvard TH Chan School of Public Health. TRANSLATIONS: For the Spanish and Portuguese translations of the abstract see Supplementary Materials section.

The impact of scaling up access to treatment and imaging modalities on global disparities in breast cancer survival: a simulation-based analysis.

BACKGROUND: Female breast cancer is the most commonly diagnosed cancer in the world, with wide variations in reported survival by country. Women in low-income and middle-income countries (LMICs) in particular face several barriers to breast cancer services, including diagnostics and treatment. We aimed to estimate the potential impact of scaling up the availability of treatment and imaging modalities on breast cancer survival globally, together with improvements in quality of care. METHODS: For this simulation-based analysis, we used a microsimulation model of global cancer survival, which accounts for the availability and stage-specific survival impact of specific treatment modalities (chemotherapy, radiotherapy, surgery, and targeted therapy), imaging modalities (ultrasound, x-ray, CT, MRI, PET, and single-photon emission computed tomography [SPECT]), and quality of cancer care, to simulate 5-year net survival for women with newly diagnosed breast cancer in 200 countries and territories in 2018. We calibrated the model to empirical data on 5-year net breast cancer survival in 2010-14 from CONCORD-3. We evaluated the potential impact of scaling up specific imaging and treatment modalities and quality of care to the mean level of high-income countries, individually and in combination. We ran 1000 simulations for each policy intervention and report the means and 95% uncertainty intervals (UIs) for all model outcomes. FINDINGS: We estimate that global 5-year net survival for women diagnosed with breast cancer in 2018 was 67·9% (95% UI 62·9-73·4) overall, with an almost 25-times difference between low-income (3·5% [0·4-10·0]) and high-income (87·0% [85·6-88·4]) countries. Among individual treatment modalities, scaling up access to surgery alone was estimated to yield the largest survival gains globally (2·7% [95% UI 0·4-8·3]), and scaling up CT alone would have the largest global impact among imaging modalities (0·5% [0·0-2·0]). Scaling up a package of traditional modalities (surgery, chemotherapy, radiotherapy, ultrasound, and x-ray) could improve global 5-year net survival to 75·6% (95% UI 70·6-79·4), with survival in low-income countries improving from 3·5% (0·4-10·0) to 28·6% (4·9-60·1). Adding concurrent improvements in quality of care could further improve global 5-year net survival to 78·2% (95% UI 74·9-80·4), with a substantial impact in low-income countries, improving net survival to 55·3% (42·2-67·8). Comprehensive scale-up of access to all modalities and improvements in quality of care could improve global 5-year net survival to 82·3% (95% UI 79·3-85·0). INTERPRETATION: Comprehensive scale-up of treatment and imaging modalities, and improvements in quality of care could improve global 5-year net breast cancer survival by nearly 15 percentage points. Scale-up of traditional modalities and quality-of-care improvements could achieve 70% of these total potential gains, with substantial impact in LMICs, providing a more feasible pathway to improving breast cancer survival in these settings even without the benefits of future investments in targeted therapy and advanced imaging. FUNDING: Harvard T H Chan School of Public Health, and National Cancer Institute P30 Cancer Center Support Grant to Memorial Sloan Kettering Cancer Center.

Cost-effectiveness of prevention and early detection of gastric cancer in Western countries.

Gastric cancer (GC) is a significant global health problem, with Helicobacter pylori infection estimated to be responsible for 89% of non-cardiac GC cases, or 78% of all GC cases. The International Agency for Research on Cancer has called for Helicobacter pylori test-and-treat strategies in countries with high rates of GC. However, for countries with low rates of GC, such as most Western countries, the balance between benefits, harms and costs of screening is less clear-cut. GC is a disease with a well-characterized precancerous process, providing the basis for primary and secondary prevention efforts. However, rigorous data assessing the impact of such interventions in Western countries are lacking. In the absence of clinical trials, modelling offers a unique approach to evaluate the potential impact of various screening and surveillance interventions. In this paper, we provide an overview of modelling studies evaluating the cost-effectiveness of GC screening and surveillance in Western countries.

Forecasting essential childhood cancer drug need: An innovative model-based approach.

BACKGROUND: Childhood cancer outcomes in low-income and middle-income countries have not kept pace with advances in care and survival in high-income countries. A contributing factor to this survival gap is unreliable access to essential drugs. METHODS: The authors created a tool (FORx ECAST) capable of predicting drug quantity and cost for 18 pediatric cancers. FORx ECAST enables users to estimate the quantity and cost of each drug based on local incidence, stage breakdown, treatment regimen, and price. Two country-specific examples are used to illustrate the capabilities of FORx ECAST to predict drug quantities. RESULTS: On the basis of domestic public-sector price data, the projected annual cost of drugs to treat childhood cancer cases is 0.8 million US dollars in Kenya and 3.0 million US dollars in China, with average median price ratios of 0.9 and 0.1, respectively, compared with costs sourced from the Management Sciences for Health (MSH) International Medical Products Price Guide. According to the cumulative chemotherapy cost, the most expensive disease to treat is acute lymphoblastic lymphoma in Kenya, but a higher relative unit cost of methotrexate makes osteosarcoma the most expensive diagnosis to treat in China. CONCLUSIONS: FORx ECAST enables needs-based estimates of childhood cancer drug volumes to inform health system planning in a wide range of contexts. It is broadly adaptable, allowing decision makers to generate results specific to their needs. The resultant estimates of drug need can help equip policymakers and health governance institutions with evidence-informed data to advance innovative procurement strategies that drive global improvements in childhood cancer drug access.

Medical imaging and nuclear medicine: a Lancet Oncology Commission.

The diagnosis and treatment of patients with cancer requires access to imaging to ensure accurate management decisions and optimal outcomes. Our global assessment of imaging and nuclear medicine resources identified substantial shortages in equipment and workforce, particularly in low-income and middle-income countries (LMICs). A microsimulation model of 11 cancers showed that the scale-up of imaging would avert 3·2% (2·46 million) of all 76·0 million deaths caused by the modelled cancers worldwide between 2020 and 2030, saving 54·92 million life-years. A comprehensive scale-up of imaging, treatment, and care quality would avert 9·55 million (12·5%) of all cancer deaths caused by the modelled cancers worldwide, saving 232·30 million life-years. Scale-up of imaging would cost US$6·84 billion in 2020-30 but yield lifetime productivity gains of $1·23 trillion worldwide, a net return of $179·19 per $1 invested. Combining the scale-up of imaging, treatment, and quality of care would provide a net benefit of $2·66 trillion and a net return of $12·43 per $1 invested. With the use of a conservative approach regarding human capital, the scale-up of imaging alone would provide a net benefit of $209·46 billion and net return of $31·61 per $1 invested. With comprehensive scale-up, the worldwide net benefit using the human capital approach is $340·42 billion and the return per dollar invested is $2·46. These improved health and economic outcomes hold true across all geographical regions. We propose actions and investments that would enhance access to imaging equipment, workforce capacity, digital technology, radiopharmaceuticals, and research and training programmes in LMICs, to produce massive health and economic benefits and reduce the burden of cancer globally.

Global costs, health benefits, and economic benefits of scaling up treatment and imaging modalities for survival of 11 cancers: a simulation-based analysis.

BACKGROUND: In addition to increased availability of treatment modalities, advanced imaging modalities are increasingly recommended to improve global cancer care. However, estimates of the costs and benefits of investments to improve cancer survival are scarce, especially for low-income and middle-income countries (LMICs). In this analysis, we aimed to estimate the costs and lifetime health and economic benefits of scaling up imaging and treatment modality packages on cancer survival, both globally and by country income group. METHODS: Using a previously developed model of global cancer survival, we estimated stage-specific cancer survival and life-years gained (accounting for competing mortality) in 200 countries and territories for patients diagnosed with one of 11 cancers (oesophagus, stomach, colon, rectum, anus, liver, pancreas, lung, breast, cervix uteri, and prostate) representing 60% of all cancer diagnoses between 2020 and 2030 (inclusive of full years). We evaluated the costs and health and economic benefits of scaling up packages of treatment (chemotherapy, surgery, radiotherapy, and targeted therapy), imaging modalities (ultrasound, x-ray, CT, MRI, PET, single-photon emission CT), and quality of care to the mean level of high-income countries, separately and in combination, compared with no scale-up. Costs and benefits are presented in 2018 US$ and discounted at 3% annually. FINDINGS: For the 11 cancers studied, we estimated that without scale-up (ie, with current availability of treatment, imaging, and quality of care) there will be 76·0 million cancer deaths (95% UI 73·9-78·6) globally for patients diagnosed between 2020 and 2030, with more than 70% of these deaths occurring in LMICs. Comprehensive scale-up of treatment, imaging, and quality of care could avert 12·5% (95% UI 9·0-16·3) of these deaths globally, ranging from 2·8% (1·8-4·3) in high-income countries to 38·2% (32·6-44·5) in low-income countries. Globally, we estimate that comprehensive scale-up would cost an additional $232·9 billion (95% UI 85·9-422·0) between 2020 and 2030 (representing a 6·9% increase in cancer treatment costs), but produce $2·9 trillion (1·8-4·0) in lifetime economic benefits, yielding a return of $12·43 (6·47-33·23) per dollar invested. Scaling up treatment and quality of care without imaging would yield a return of $6·15 (2·66-16·71) per dollar invested and avert 7·0% (3·9-10·3) of cancer deaths worldwide. INTERPRETATION: Simultaneous investment in cancer treatment, imaging, and quality of care could yield substantial health and economic benefits, especially in LMICs. These results provide a compelling rationale for the value of investing in the global scale-up of cancer care. FUNDING: Harvard TH Chan School of Public Health and National Cancer Institute.

What are the volume and budget needs to provide chemotherapy to all children with acute lymphoblastic leukaemia in Thailand? Development and application of an estimation tool.

OBJECTIVE: Insufficient access to anticancer medicines may contribute to the wide survival differences of children with cancers across the globe. We developed a tool to estimate the volume of medicines and budget requirements to provide chemotherapy to children with acute lymphoblastic leukaemia (ALL). DESIGN: Development and application of an estimation tool. SETTING: Paediatric oncology hospital departments in Thailand. PARTICIPANTS: 318 children aged 0-14 years diagnosed with ALL and 215 children with undiagnosed ALL. INTERVENTIONS: Estimates of volume and budget requirements for administering a full course of chemotherapy for ALL and a further course for children who relapse, according to National Treatment Guidelines. PRIMARY AND SECONDARY OUTCOME MEASURES: Primary outcome measures were the volume (mg) and cost (US$) of medicines needed to treat children with ALL. For medicines whose main indication is paediatric ALL (asparaginase and 6-mercaptopurine), we estimated the difference between volume needed and actual sales in 2017 (secondary outcome). RESULTS: Ten anticancer medicines and four chemoprotective agents are needed for the treatment of paediatric ALL according to the Thai treatment guidelines. Of these 14 medicines, 13 are included in the WHO essential medicines list for children. All are available as generics. We estimated that essential chemotherapy and chemoprotective agents to treat all children diagnosed with ALL in Thailand in 2017 would cost US$ 814 952 (US$ 1 365 422 for diagnosed and undiagnosed children), which corresponds to 0.005% (0.008%) of the country's total health expenditure. The volumes of asparaginase and 6-mercaptopurine available on the Thai market in 2017 were more than sufficient (2.3 and 1.5 times the amounts needed, respectively) to treat all children diagnosed with ALL. CONCLUSIONS: Procuring sufficient quantities of essential medicines to treat children with ALL requires relatively modest resources. Medicine cost should not be a major barrier to ALL treatment in similar settings.

Cost-Effectiveness of the International Late Effects of Childhood Cancer Guideline Harmonization Group Screening Guidelines to Prevent Heart Failure in Survivors of Childhood Cancer.

PURPOSE: Survivors of childhood cancer treated with anthracyclines and/or chest-directed radiation are at increased risk for heart failure (HF). The International Late Effects of Childhood Cancer Guideline Harmonization Group (IGHG) recommends risk-based screening echocardiograms, but evidence supporting its frequency and cost-effectiveness is limited. PATIENTS AND METHODS: Using the Childhood Cancer Survivor Study and St Jude Lifetime Cohort, we developed a microsimulation model of the clinical course of HF. We estimated long-term health outcomes and economic impact of screening according to IGHG-defined risk groups (low [doxorubicin-equivalent anthracycline dose of 1-99 mg/m2 and/or radiotherapy < 15 Gy], moderate [100 to < 250 mg/m2 or 15 to < 35 Gy], or high [≥ 250 mg/m2 or ≥ 35 Gy or both ≥ 100 mg/m2 and ≥ 15 Gy]). We compared 1-, 2-, 5-, and 10-year interval-based screening with no screening. Screening performance and treatment effectiveness were estimated based on published studies. Costs and quality-of-life weights were based on national averages and published reports. Outcomes included lifetime HF risk, quality-adjusted life-years (QALYs), lifetime costs, and incremental cost-effectiveness ratios (ICERs). Strategies with ICERs < $100,000 per QALY gained were considered cost-effective. RESULTS: Among the IGHG risk groups, cumulative lifetime risks of HF without screening were 36.7% (high risk), 24.7% (moderate risk), and 16.9% (low risk). Routine screening reduced this risk by 4% to 11%, depending on frequency. Screening every 2, 5, and 10 years was cost-effective for high-risk survivors, and every 5 and 10 years for moderate-risk survivors. In contrast, ICERs were > $175,000 per QALY gained for all strategies for low-risk survivors, representing approximately 40% of those for whom screening is currently recommended. CONCLUSION: Our findings suggest that refinement of recommended screening strategies for IGHG high- and low-risk survivors is needed, including careful reconsideration of discontinuing asymptomatic left ventricular dysfunction and HF screening in low-risk survivors.

Estimating the impact of treatment and imaging modalities on 5-year net survival of 11 cancers in 200 countries: a simulation-based analysis.

BACKGROUND: Accurate survival estimates are important for cancer control planning. Although observed survival estimates are unavailable for many countries, where they are available, wide variations are reported. Understanding the impact of specific treatment and imaging modalities can help decision makers to effectively allocate resources to improve cancer survival in their local context. METHODS: We developed a microsimulation model of stage-specific cancer survival in 200 countries and territories for 11 cancers (oesophagus, stomach, colon, rectum, anus, liver, pancreas, lung, breast, cervix uteri, and prostate) comprising 60% of global diagnosed cancer cases. The model accounts for country-specific availability of treatment (chemotherapy, surgery, radiotherapy, and targeted therapy) and imaging modalities (ultrasound, x-ray, CT, MRI, PET, single-photon emission CT), as well as quality of care. We calibrated the model to reported survival estimates from CONCORD-3 (which reports global trends in cancer survival in 2000-14). We estimated 5-year net survival for diagnosed cancers in each country or territory and estimated potential survival gains from increasing the availability of individual treatment and imaging modalities, and more comprehensive packages of scale-up of these interventions. We report the mean and 95% uncertainty intervals (UIs) for all outcomes, calculated as the 2·5 and 97·5 percentiles of the simulation results. FINDINGS: The estimated global 5-year net survival for all 11 cancers combined is 42·6% (95% uncertainty interval 40·3-44·3), with survival in high-income countries being an average of 12 times (range 4-17) higher than that in low-income countries. Expanding availability of surgery or radiotherapy or improving quality of care would yield the largest survival gains in low-income (2·5-3·4 percentage point increase in survival) and lower-middle-income countries (2·4-6·1 percentage point increase), whereas upper-middle-income and high-income countries are more likely to benefit from improved availability of targeted therapy (0·7 percentage point increase for upper-middle income and 0·4 percentage point increase for high income). Investing in medical imaging will also be necessary to achieve substantial survival gains, with traditional modalities estimated to provide the largest gains in low-income settings, while MRI and PET would yield the largest gains in higher-income countries. Simultaneous expansion of treatment, imaging, and quality of care could improve 5-year net survival by more than ten times in low-income countries (3·8% [95% UI 0·5-9·2] to 45·2% [40·2-52·1]) and could more than double 5-year net survival in lower-middle-income countries (20·1% [7·2-31·7] to 47·1% [42·8-50·8]). INTERPRETATION: Scaling up both treatment and imaging availability could yield synergistic survival gains for patients with cancer. Expanding traditional modalities in lower-income settings might be a feasible pathway to improve survival before scaling up more modern technologies. FUNDING: Harvard T H Chan School of Public Health.

The role and contribution of treatment and imaging modalities in global cervical cancer management: survival estimates from a simulation-based analysis.

BACKGROUND: Cervical cancer is the fourth most common cancer among women worldwide, causing more than 300 000 deaths globally each year. In addition to screening and prevention, effective cancer treatment is needed to reduce cervical cancer mortality. We discuss the role of imaging in cervical cancer management and estimate the potential survival effect of scaling up imaging in several different contexts. METHODS: Using a previously developed microsimulation model of global cancer survival, we estimated stage-specific cervical cancer 5-year net survival in 200 countries and territories. We evaluated the potential survival effect of scaling up treatment (chemotherapy, surgery, radiotherapy, and targeted therapy), and imaging modalities (ultrasound, x-ray, CT, MRI, PET, and single photon emission CT [SPECT]) to the mean level of high-income countries, both individually and in combination. FINDINGS: We estimate global cervical cancer 5-year net survival as 42·1% (95% uncertainty interval [UI] 33·8-48·5). Among individual imaging modalities, expanding MRI would yield the largest 5-year survival gains globally (data are absolute percentage point increase in survival 0·6, 95% UI 0·1-2·1), scaling up ultrasound would yield the largest gains in low-income countries (0·5, 0·0-3·7), expanding CT and x-ray would have the greatest effect in Latin America (0·8, 0·0-3·4) and Oceania (0·4, 0·0-3·2), and expanding PET would yield the largest gains in high-income countries (0·2, 0·0-0·8). Scaling up SPECT did not show major changes in any region. Among individual treatment modalities, scaling up radiotherapy would yield the largest absolute percentage point gains in low-income countries (5·2, 0·3-13·5), and expanding surgery would have the largest effect in lower-middle-income countries (7·4, 0·3-21·1) and upper-middle-income countries (0·8, 0·0-2·9). Estimated survival gains in high-income countries were very modest. However, the gains from expanding any single treatment or imaging modality individually were small across all income levels and geographical settings. Scaling up all treatment modalities could improve global 5-year net survival to 52·4% (95% UI 44·6-62·0). In addition to expanding treatment, improving quality of care could raise survival to 57·5% (51·2-63·5), and the cumulative effect of scaling up all imaging modalities together with expanded treatment and quality of care could improve 5-year net survival for cervical cancer to 62·5% (57·7-67·8). INTERPRETATION: Comprehensive scale-up of treatment, imaging, and quality of care could substantially improve global cervical cancer 5-year net survival, with quality of care and imaging improvements each contributing about 25% of the total potential gains. These findings suggest that a narrow focus on the availability of treatment modalities could forgo substantial survival gains. Investments in imaging equipment, personnel, and quality of care efforts will also be needed to successfully scale up cervical cancer treatment worldwide. FUNDING: Harvard T H Chan School of Public Health and National Cancer Institute.

Diagnostic performance of conventional and advanced imaging modalities for assessing newly diagnosed cervical cancer: systematic review and meta-analysis.

OBJECTIVES: To review the diagnostic performance of contemporary imaging modalities for determining local disease extent and nodal metastasis in patients with newly diagnosed cervical cancer. METHODS: Pubmed and Embase databases were searched for studies published from 2000 to 2019 that used ultrasound (US), CT, MRI, and/or PET for evaluating various aspects of local extent and nodal metastasis in patients with newly diagnosed cervical cancer. Sensitivities and specificities from the studies were meta-analytically pooled using bivariate and hierarchical modeling. RESULTS: Of 1311 studies identified in the search, 115 studies with 13,999 patients were included. MRI was the most extensively studied modality (MRI, CT, US, and PET were evaluated in 78, 12, 9, and 43 studies, respectively). Pooled sensitivities and specificities of MRI for assessing all aspects of local extent ranged between 0.71-0.88 and 0.86-0.95, respectively. In assessing parametrial invasion (PMI), US demonstrated pooled sensitivity and specificity of 0.67 and 0.94, respectively-performance levels comparable with those found for MRI. MRI, CT, and PET performed comparably for assessing nodal metastasis, with low sensitivity (0.29-0.69) but high specificity (0.88-0.98), even when stratified to anatomical location (pelvic or paraaortic) and level of analysis (per patient vs. per site). CONCLUSIONS: MRI is the method of choice for assessing any aspect of local extent, but where not available, US could be of value, particularly for assessing PMI. CT, MRI, and PET all have high specificity but poor sensitivity for the detection of lymph node metastases. KEY POINTS: • Magnetic resonance imaging is the method of choice for assessing local extent. • Ultrasound may be helpful in determining parametrial invasion, especially in lower-resourced countries. • Computed tomography, magnetic resonance imaging, and positron emission tomography perform similarly for assessing lymph node metastasis, with high specificity but low sensitivity.

Sustainable care for children with cancer: a Lancet Oncology Commission.

We estimate that there will be 13·7 million new cases of childhood cancer globally between 2020 and 2050. At current levels of health system performance (including access and referral), 6·1 million (44·9%) of these children will be undiagnosed. Between 2020 and 2050, 11·1 million children will die from cancer if no additional investments are made to improve access to health-care services or childhood cancer treatment. Of this total, 9·3 million children (84·1%) will be in low-income and lower-middle-income countries. This burden could be vastly reduced with new funding to scale up cost-effective interventions. Simultaneous comprehensive scale-up of interventions could avert 6·2 million deaths in children with cancer in this period, more than half (56·1%) of the total number of deaths otherwise projected. Taking excess mortality risk into consideration, this reduction in the number of deaths is projected to produce a gain of 318 million life-years. In addition, the global lifetime productivity gains of US$2580 billion in 2020-50 would be four times greater than the cumulative treatment costs of $594 billion, producing a net benefit of $1986 billion on the global investment: a net return of $3 for every $1 invested. In sum, the burden of childhood cancer, which has been grossly underestimated in the past, can be effectively diminished to realise massive health and economic benefits and to avert millions of needless deaths.

Life Expectancy of Adult Survivors of Childhood Cancer Over 3 Decades.

Importance: Advances in childhood and adolescent cancer treatment have been associated with increased rates of cure during the past 3 decades; however, improvement in adult life expectancy for these individuals has not yet been reported. Objectives: To project long-term survival and assess whether life expectancy will improve among adult survivors of childhood cancer who were treated in more recent decades. Design, Setting, and Participants: A microsimulation model of competing mortality risks was developed using data from the Childhood Cancer Survivor Study on 5-year survivors of childhood cancer diagnosed between 1970 and 1999. The model included (1) late recurrence, (2) treatment-related late effects (health-related [subsequent cancers, cardiac events, pulmonary conditions, and other] and external causes), and (3) US background mortality rates. Exposures: Treatment subgroups (no treatment or surgery only, chemotherapy alone, radiotherapy alone, and radiotherapy with chemotherapy) and individuals with acute lymphoblastic leukemia during childhood by era (1970-1979, 1980-1989, and 1990-1999). Main Outcomes and Measures: Conditional life expectancy (defined as the number of years a 5-year survivor can expect to live), cumulative cause-specific mortality risk, and 10-year mortality risks conditional on attaining ages of 30, 40, 50, and 60 years. Results: Among the hypothetical cohort of 5-year survivors of childhood cancer representative of the Childhood Cancer Survivor Study participants (44% female and 56% male; mean [SD] age at diagnosis, 7.3 [5.6] years), conditional life expectancy was 48.5 years (95% uncertainty interval [UI], 47.6-49.6 years) for 5-year survivors diagnosed in 1970-1979, 53.7 years (95% UI, 52.6-54.7 years) for those diagnosed in 1980-1989, and 57.1 years (95% UI, 55.9-58.1 years) for those diagnosed in 1990-1999. Compared with individuals without a history of cancer, these results represented a gap in life expectancy of 25% (95% UI, 24%-27%) (16.5 years [95% UI, 15.5-17.5 years]) for those diagnosed in 1970-1979, 19% (95% UI, 17%-20%) (12.3 years [95% UI, 11.3-13.4 years]) for those diagnosed in 1980-1989, and 14% (95% UI, 13%-16%) (9.2 years [95% UI, 8.3-10.4 years]) for those diagnosed in 1990-1999. During the 3 decades, the proportion of survivors treated with chemotherapy alone increased (from 18% in 1970-1979 to 54% in 1990-1999), and the life expectancy gap in this chemotherapy-alone group decreased from 11.0 years (95% UI, 9.0-13.1 years) to 6.0 years (95% UI, 4.5-7.6 years). In contrast, during the same time frame, only modest improvements in the gap in life expectancy were projected for survivors treated with radiotherapy (21.0 years [95% UI, 18.5-23.2 years] to 17.6 years [95% UI, 14.2-21.2 years]) or with radiotherapy and chemotherapy (17.9 years [95% UI, 16.7-19.2 years] to 14.8 years [95% UI, 13.1-16.7 years]). For the largest group of survivors by diagnosis-those with acute lymphoblastic leukemia-the gap in life expectancy decreased from 14.7 years (95% UI, 12.8-16.5 years) in 1970-1979 to 8.0 years (95% UI, 6.2-9.7 years). Conclusions and Relevance: Evolving treatment approaches are projected to be associated with improved life expectancy after treatment for pediatric cancer, in particular among those who received chemotherapy alone for their childhood cancer diagnosis. Despite improvements, survivors remain at risk for shorter lifespans, especially when radiotherapy was included as part of their childhood cancer treatment.

Global childhood cancer survival estimates and priority-setting: a simulation-based analysis.

BACKGROUND: Accurate childhood cancer survival estimates are crucial for policy makers and clinicians for priority-setting and planning decisions. However, observed survival estimates are lacking for many countries, and when available, wide variation in outcomes is reported. Understanding the barriers to optimising survival can help improve childhood cancer outcomes. We aimed to provide estimates of global childhood cancer survival, accounting for the impact of multiple factors that affect cancer outcomes in children. METHODS: We developed a microsimulation model to simulate childhood cancer survival for 200 countries and territories worldwide, accounting for clinical and epidemiologic factors, including country-specific treatment variables, such as availability of chemotherapy, radiation, and surgery. To ensure model results were consistent with reported survival data, we calibrated the model to estimates from the CONCORD-2 and CONCORD-3 studies using an Approximate Bayesian Computation approach. We estimated 5-year net survival for diagnosed cases of childhood cancer in each country and territory and estimated potential survival gains of seven policy interventions focused on improving treatment availability and delivery (ie, increasing the availability of chemotherapy, radiation, general surgery, neurosurgery, or ophthalmic surgery, reducing treatment abandonment, and improving the quality of care to the mean of high-income countries) implemented in isolation or as packages. FINDINGS: Our model estimated that, for diagnosed cases, global 5-year net childhood cancer survival is currently 37·4% (95% uncertainty interval 34·7-39·8), with large variation by region, ranging from 8·1% (4·4-13·7) in eastern Africa to 83·0% (81·6-84·4) in North America. Among the seven policy interventions modelled, each individually provided small gains, increasing global 5-year net survival to between 38·4% (35·8-40·9) and 44·6% (41·7-47·4). 5-year net survival increased more substantially when policy interventions were bundled into packages that improved service delivery (5-year net survival 50·2% [47·3-53·0]) or that expanded treatment access (54·1% [50·1-58·5]). A comprehensive systems approach consisting of all policy interventions yielded superadditive gains with a global 5-year net survival of 53·6% (51·5-55·6) at 50% scale-up and 80·8% (79·5-82·1) at full implementation. INTERPRETATION: Childhood cancer survival varies widely by region, with especially poor survival in Africa. Although expanding access to treatment (chemotherapy, radiation, and surgery) and addressing financial toxicity are essential, investments that improve the quality of care, at both the health-system and facility level, are needed to improve childhood cancer outcomes globally. FUNDING: Boston Children's Hospital, Dana-Farber Cancer Institute, Harvard TH Chan School of Public Health, Harvard Medical School, National Cancer Institute, SickKids, St Jude Children's Research Hospital, Union for International Cancer Control, Children with Cancer UK Davidson and O'Gorman Fellowship.

Estimating the total incidence of global childhood cancer: a simulation-based analysis.

BACKGROUND: Accurate estimates of childhood cancer incidence are important for policy makers to inform priority setting and planning decisions. However, many countries do not have cancer registries that quantify the incidence of childhood cancer. Moreover, even when registries do exist, they might substantially underestimate the true incidence, since children with cancer might not be diagnosed. We therefore aimed to provide estimates of total childhood cancer incidence accounting for underdiagnosis. METHODS: We developed a microsimulation model to simulate childhood cancer incidence for 200 countries and territories worldwide, taking into account trends in population growth and urbanicity, geographical variation in cancer incidence, and health system barriers to access and referral that contribute to underdiagnosis. To ensure model results were consistent with epidemiological data, we calibrated the model to publicly available cancer registry data using a Bayesian approach in which the observed data are fixed and the model parameters (cancer incidence and probabilities of health system access and referral) are random variables. We estimated the total incidence of childhood cancer (diagnosed and undiagnosed) in each country in 2015 and projected the number of cases from 2015 to 2030. FINDINGS: Our model estimated that there were 397 000 (95% uncertainty interval [UI] 377 000-426 000) incident cases of childhood cancer worldwide in 2015, of which only 224 000 (95% UI 216 000-237 000) were diagnosed. This finding suggests that 43% (172 000 of 397 000) of childhood cancer cases were undiagnosed globally, with substantial variation by region, ranging from 3% in western Europe (120 of 4300) and North America (300 of 10 900) to 57% (43 000 of 76 000) in western Africa. In south Asia (including southeastern Asia and south-central Asia), the overall proportion of undiagnosed cases was estimated to be 49% (67 000 of 137 000). Taking into account population projections, we estimated that there will be 6·7 million (95% UI 6·3-7·2) cases of childhood cancer worldwide from 2015 to 2030. At current levels of health system performance, we estimated that 2·9 million (95% UI 2·7-3·3) cases of childhood cancer will be missed between 2015 and 2030. INTERPRETATION: Childhood cancer is substantially underdiagnosed, especially in south Asia and sub-Saharan Africa (including western, eastern, and southern Africa). In addition to improving treatment for childhood cancer, health systems must be strengthened to accurately diagnose and effectively care for all children with cancer. As countries expand universal health coverage, these estimates of total incidence will hopefully help guide efforts to appropriately increase health system capacity to ensure access to effective childhood cancer care. FUNDING: Boston Children's Hospital, Dana-Farber Cancer Institute, Harvard T H Chan School of Public Health, Harvard Medical School, National Cancer Institute, SickKids, St Jude Children's Research Hospital, and Union for International Cancer Control.

Chronic Conditions and Utility-Based Health-Related Quality of Life in Adult Childhood Cancer Survivors.

Health utility, a summary measure of quality of life, has not been previously used to compare outcomes among childhood cancer survivors and individuals without a cancer history. We estimated health utility (0, death; 1, perfect health) using the Short Form-6D (SF-6D) in survivors (n = 7105) and siblings of survivors (n = 372) (using the Childhood Cancer Survivor Study cohort) and the general population (n = 12 803) (using the Medical Expenditures Panel Survey). Survivors had statistically significantly lower SF-6D scores than the general population (mean = 0.769, 95% confidence interval [CI] = 0.766 to 0.771, vs mean = 0.809, 95% CI = 0.806 to 0.813, respectively, ITALIC! P< .001, two-sided). Young adult survivors (age 18-29 years) reported scores comparable with general population estimates for people age 40 to 49 years. Among survivors, SF-6D scores were largely determined by number and severity of chronic conditions. No clinically meaningful differences were identified between siblings and the general population (mean = 0.793, 95% CI = 0.782 to 0.805, vs mean = 0.809, 95% CI = 0.806 to 0.813, respectively). This analysis illustrates the importance of chronic conditions on long-term survivor quality of life and provides encouraging results on sibling well-being. Preference-based utilities are informative tools for outcomes research in cancer survivors.