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.
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.
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.
To quantify the potential population-wide costs, number of individuals reached, and impact on obesity of five effective interventions to reduce children's television viewing if implemented nationally. Utilizing evidence from systematic reviews, the Childhood Obesity Intervention Cost Effectiveness Study (CHOICES) microsimulation model estimated the cost, population reach, and impact on childhood obesity from 2020 to 2030 of five hypothetical policy strategies to reduce the negative impact of children's TV exposure: (1) eliminating the tax deductibility of food and beverage advertising; (2) targeting TV reduction during home visiting programs; (3) motivational interviewing to reduce home television time at Women, Infants, and Children (WIC) clinic visits; (4) adoption of a television-reduction curriculum in child care; and (5) limiting noneducational television in licensed child care settings. Eliminating the tax deductibility of food advertising could reach the most children [106 million, 95% uncertainty interval (UI): 105-107 million], prevent the most cases of obesity (78,700, 95% UI: 30,200-130,000), and save more in health care costs than it costs to implement. Strategies targeting young children in child care and WIC also cost little to implement (between $0.19 and $32.73 per child reached), and, although reaching fewer children because of the restricted age range, were estimated to prevent between 25,500 (95% UI: 4600-59,300) and 35,400 (95% UI: 13,200-62,100) cases of obesity. Home visiting to reduce television viewing had high costs and a low reach. Interventions to reduce television exposure across a range of settings, if implemented widely, could help prevent childhood obesity in the population at relatively low cost.
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 (FOR ECAST) capable of predicting drug quantity and cost for 18 pediatric cancers. FOR 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 FOR 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: FOR 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.
BACKGROUND: Estimates of health care costs associated with excess weight are needed to inform the development of cost-effective obesity prevention efforts. However, commonly used cost estimates are not sensitive to changes in weight across the entire body mass index (BMI) distribution as they are often based on discrete BMI categories.
METHODS: We estimated continuous BMI-related health care expenditures using data from the Medical Expenditure Panel Survey (MEPS) 2011-2016 for 175,726 respondents. We adjusted BMI for self-report bias using data from the National Health and Nutrition Examination Survey (NHANES) 2011-2016, and controlled for potential confounding between BMI and medical expenditures using a two-part model. Costs are reported in $US 2019.
RESULTS: We found a J-shaped curve of medical expenditures by BMI, with higher costs for females and the lowest expenditures occurring at a BMI of 20.5 for adult females and 23.5 for adult males. Over 30 units of BMI, each one-unit BMI increase was associated with an additional cost of $253 (95% CI $167-$347) per person. Among adults, obesity was associated with $1,861 (95% CI $1,656-$2,053) excess annual medical costs per person, accounting for $172.74 billion (95% CI $153.70-$190.61) of annual expenditures. Severe obesity was associated with excess costs of $3,097 (95% CI $2,777-$3,413) per adult. Among children, obesity was associated with $116 (95% CI $14-$201) excess costs per person and $1.32 billion (95% CI $0.16-$2.29) of medical spending, with severe obesity associated with $310 (95% CI $124-$474) excess costs per child.
CONCLUSIONS: Higher health care costs are associated with excess body weight across a broad range of ages and BMI levels, and are especially high for people with severe obesity. These findings highlight the importance of promoting a healthy weight for the entire population while also targeting efforts to prevent extreme weight gain over the life course.
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 $2·46. These improved health and economic outcomes hold true across all geographical regions. We propose actions and investments that would enhance access to imaging equipment, workforce capacity, digital technology, radiopharmaceuticals, and research and training programmes in LMICs, to produce massive health and economic benefits and reduce the burden of cancer globally.
BACKGROUND: In addition to increased availability of treatment modalities, advanced imaging modalities are increasingly recommended to improve global cancer care. However, estimates of the costs and benefits of investments to improve cancer survival are scarce, especially for low-income and middle-income countries (LMICs). In this analysis, we aimed to estimate the costs and lifetime health and economic benefits of scaling up imaging and treatment modality packages on cancer survival, both globally and by country income group.
METHODS: Using a previously developed model of global cancer survival, we estimated stage-specific cancer survival and life-years gained (accounting for competing mortality) in 200 countries and territories for patients diagnosed with one of 11 cancers (oesophagus, stomach, colon, rectum, anus, liver, pancreas, lung, breast, cervix uteri, and prostate) representing 60% of all cancer diagnoses between 2020 and 2030 (inclusive of full years). We evaluated the costs and health and economic benefits of scaling up packages of treatment (chemotherapy, surgery, radiotherapy, and targeted therapy), imaging modalities (ultrasound, x-ray, CT, MRI, PET, single-photon emission CT), and quality of care to the mean level of high-income countries, separately and in combination, compared with no scale-up. Costs and benefits are presented in 2018 US$ 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.
BACKGROUND: Electronic health record (EHR) data contain longitudinal patient information and standardized diagnostic codes. EHR data may be useful for estimating transition probabilities for state-transition models, but no guidelines exist on appropriate methods. We applied 3 potential methods to estimate transition probabilities from EHR data, using pediatric eating disorders (EDs) as a case study.
METHODS: We obtained EHR data from PEDsnet, which includes 8 US children's hospitals. Data included inpatient, outpatient, and emergency department visits for all patients with an ED. We mapped diagnoses to 3 ED health states: anorexia nervosa, bulimia nervosa, and other specified feeding or eating disorder. We estimated 1-y transition probabilities for males and females using 3 approaches: simple first-last proportions, a multistate Markov (MSM) model, and independent survival models.
RESULTS: Transition probability estimates varied widely between approaches. The first-last proportion approach estimated higher probabilities of remaining in the same health state, while the MSM and independent survival approaches estimated higher probabilities of transitioning to a different health state. All estimates differed substantially from published literature.
LIMITATIONS: As a source of health state information, EHR data are incomplete and sometimes inaccurate. EHR data were especially challenging for EDs, limiting the estimation and interpretation of transition probabilities.
CONCLUSIONS: The 3 approaches produced very different transition probability estimates. Estimates varied considerably from published literature and were rescaled and calibrated for use in a microsimulation model. Estimation of transition probabilities from EHR data may be more promising for diseases that are well documented in the EHR. Furthermore, clinicians and health systems should work to improve documentation of ED in the EHR. Further research is needed on methods for using EHR data to inform transition probabilities.
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.
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/m and/or radiotherapy < 15 Gy], moderate [100 to < 250 mg/m or 15 to < 35 Gy], or high [≥ 250 mg/m or ≥ 35 Gy or both ≥ 100 mg/m 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.
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.
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.
The Healthy, Hunger-Free Kids Act of 2010 strengthened nutrition standards for meals and beverages provided through the National School Lunch, Breakfast, and Smart Snacks Programs, affecting fifty million children daily at 99,000 schools. The legislation's impact on childhood obesity is unknown. We tested whether the legislation was associated with reductions in child obesity risk over time using an interrupted time series design for 2003-18 among 173,013 youth in the National Survey of Children's Health. We found no significant association between the legislation and childhood obesity trends overall. For children in poverty, however, the risk of obesity declined substantially each year after the act's implementation, translating to a 47 percent reduction in obesity prevalence in 2018 from what would have been expected without the legislation. These results suggest that the Healthy, Hunger-Free Kids Act's science-based nutritional standards should be maintained to support healthy growth, especially among children living in poverty.
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.
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.
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.
BACKGROUND: Although the national obesity epidemic has been well documented, less is known about obesity at the U.S. state level. Current estimates are based on body measures reported by persons themselves that underestimate the prevalence of obesity, especially severe obesity.
METHODS: We developed methods to correct for self-reporting bias and to estimate state-specific and demographic subgroup-specific trends and projections of the prevalence of categories of body-mass index (BMI). BMI data reported by 6,264,226 adults (18 years of age or older) who participated in the Behavioral Risk Factor Surveillance System Survey (1993-1994 and 1999-2016) were obtained and corrected for quantile-specific self-reporting bias with the use of measured data from 57,131 adults who participated in the National Health and Nutrition Examination Survey. We fitted multinomial regressions for each state and subgroup to estimate the prevalence of four BMI categories from 1990 through 2030: underweight or normal weight (BMI [the weight in kilograms divided by the square of the height in meters], <25), overweight (25 to <30), moderate obesity (30 to <35), and severe obesity (≥35). We evaluated the accuracy of our approach using data from 1990 through 2010 to predict 2016 outcomes.
RESULTS: The findings from our approach suggest with high predictive accuracy that by 2030 nearly 1 in 2 adults will have obesity (48.9%; 95% confidence interval [CI], 47.7 to 50.1), and the prevalence will be higher than 50% in 29 states and not below 35% in any state. Nearly 1 in 4 adults is projected to have severe obesity by 2030 (24.2%; 95% CI, 22.9 to 25.5), and the prevalence will be higher than 25% in 25 states. We predict that, nationally, severe obesity is likely to become the most common BMI category among women (27.6%; 95% CI, 26.1 to 29.2), non-Hispanic black adults (31.7%; 95% CI, 29.9 to 33.4), and low-income adults (31.7%; 95% CI, 30.2 to 33.2).
CONCLUSIONS: Our analysis indicates that the prevalence of adult obesity and severe obesity will continue to increase nationwide, with large disparities across states and demographic subgroups. (Funded by the JPB Foundation.).
OBJECTIVE: This study aimed to estimate the cost-effectiveness and impact on childhood obesity of installation of chilled water dispensers ("water jets") on school lunch lines and to compare water jets' cost, reach, and impact on water consumption with three additional strategies.
METHODS: The Childhood Obesity Intervention Cost Effectiveness Study(CHOICES) microsimulation model estimated the cost-effectiveness of water jets on US childhood obesity cases prevented in 2025. Also estimated were the cost, number of children reached, and impact on water consumption of the installation of water jets and three other strategies.
RESULTS: Installing water jets on school lunch lines was projected to reach 29.6 million children (95% uncertainty interval [UI]: 29.4 million-29.8 million), cost $4.25 (95% UI: $2.74-$5.69) per child, prevent 179,550 cases of childhood obesity in 2025 (95% UI: 101,970-257,870), and save $0.31 in health care costs per dollar invested (95% UI: $0.15-$0.55). In the secondary analysis, installing cup dispensers next to existing water fountains was the least costly but also had the lowest population reach.
CONCLUSIONS: Installating water jet dispensers on school lunch lines could also save almost half of the dollars needed for implementation via a reduction in obesity-related health care costs. School-based interventions to promote drinking water may be relatively inexpensive strategies for improving child health.