Measure Of Cancer Burden Research Articles

Cancer lethality: an important burden metric to consider for the allocation of clinical trial research funding from all sources

<h3>Objectives:</h3> To identify trends and discrepancies between the number of clinical trials funded by public, industry, and other (individuals, universities, and community-based) organizations and measures of individual- and population-level cancer burden. <h3>Methods:</h3> Clinicaltrials.gov was queried for US trials initiated from 2007-2017 in 18 cancer types. For each cancer, incidence and mortality rates were obtained from the CDC, and person years of life lost (YLL) was obtained from the SEER database. Trials were categorized by funding sources and analyzed by measures of cancer burden: incidence (I), mortality (M), YLL, and lethality (L, years of life lost per new diagnosis). Standardized ratios of the number of new studies each year to cancer burden metrics were generated. These ratios were labeled as studies funded by public sources (#P/I, #P/M, #P/YLL, #P/L), industry sources (#I/I, #I/M, #I/YLL, #I/L), and other sources (#O/I, #O/M, #O/YLL, #O/L). Mean annual ratios for GYN cancers were compared to other cancers using Wilcoxon rank-sum tests. Rates of change (ROC) for these ratios over the 11-year period for each funding source were analyzed by linear regression. <h3>Results:</h3> Breast cancer was the most studied cancer among public, industry, and other funded sources, averaging 71.3, 101.6, and 101.0 new studies per year. For new studies in GYN cancers, ovary ranks 7th, 7th, and 10th; cervix 13th, 16th, and 13th; uterus 12th, 14th, and 12th. While breast and prostate cancers rank 11th and 17th in Lethality, the mean ratios for breast (#P/L 22.12, #I/L 31.84, #O/L 31.68, Figure 1) and prostate (#P/L 22.61, #I/L 33.37, #O/L 27.21) are the two highest across all 3 funding sources. Ovarian cancer ranks 4th in Lethality with 11.14 years of life lost per new diagnosis, yet it ranks 12th in mean #P/L (2.086 - lower than 10 others at p<0.05), 10th in #I/L (2.886 - lower than 9 others at p<0.05), and 14th in #O/L (1.557 - lower than 13 others at p<0.05). Cervical cancer is the 7th most lethal, but its ratios rank 16th in all funding categories (#P/L 1.373, #I/L 0.886, #O/L 1.108). Uterine cancer is the 12th most lethal with ratios ranking 8th (#P/L 5.755) 11th (#I/L 3.387), and 12th (#O/L 4.246). Over the 11-year period, the mean #P/L ratios for 4 of 18 cancers (uterus, testicular, brain, esophagus) had a significant negative slope or rate of change (p<0.05). Bladder cancer had the only positive ROC. For #I/L over 11 years, 9 of 18 cancers, including ovarian, had a significant positive ROC. None had a negative ROC. In other funded studies, 7 cancers had a significant positive ROC, and 11 were stagnant. For GYN cancers across all four cancer burden parameters, uterine showed a significant negative slope in the number of public funded studies and ovarian cancer had a significant positive slope for industry funded studies. <h3>Conclusions:</h3> GYN cancers have significantly fewer initiated studies when compared by Lethality across funding categories. Lethality incorporates incidence, mortality, and YLL. It is an important measure of individual cancer burden and should be considered for funding allocation. Within all cancer sites, there is a significant trend towards rising industry and other funded trials and a trend towards decreasing or stagnating number of public funded studies. This data can be used to investigate reasons for the differential allocation of resources regarding clinical trial initiation.

SCAN360: A Resource for a 360-Degree View of Cancer Prevention, Risk, and Survival.

SCAN360, an interactive web platform aiming to provide a “360-degree view” of factors that drive cancer, calculates and integrates several measures of cancer burden from the Florida Cancer Data System, the state’s cancer registry, from 2012 to 2016 with cancer risk factors, clinical factors, and social determinants of health on multiple levels of geography — ranging from the entire state to the neighborhood. Integrating various sources of data, the web platform visualizes numerous indicators, including sociodemographic characteristics, cancer histology and staging, risk behaviors, screening behavior, environmental factors, hazardous sites, health insurance access, prevalence of potential comorbidities, housing characteristics, and levels of residential segregation, through maps and easy-to-interpret graphs. By walking through an example of a practical use, we show that SCAN360 provides data that are easily accessible to public health professionals, decision makers, and researchers and can assist them with identifying potential drivers of cancer burden on a localized level.

The relationship between government research funding and the cancer burden in South Korea: implications for prioritising health research

BackgroundIn this study, we aimed to assess health research funding allocation in South Korea by analysing the relationship between government funding and disease burden in South Korea, specifically focusing on cancers.MethodsThe relationship between research funding and the cancer burden, measured in disability-adjusted life-years (DALYs), was analysed using a linear regression method over a 10-year interval. Funding information on 25 types of cancer was obtained from the National Science and Technology Information Service portal in South Korea. Measures of cancer burden were obtained from Global Burden of Disease studies. The funding predictions were derived from regression analysis and compared with actual funding allocations. In addition, we evaluated how the funding distribution reflected long-term changes in the burden and the burden specific to South Korea compared with global values.ResultsKorean funding in four periods, 2005–2007, 2008–2010, 2011–2013 and 2015–2017, were associated with the cancer burden in 2003, 2006, 2009 and 2013, respectively. For DALYs, the correlation coefficients were 0.79 and 0.82 in 2003 and 2013, respectively, which were higher than the values from other countries. However, the changes in DALYs (1990–2006) were not associated with the funding changes (from 2005 to 2007 to 2015–2017). In addition, the value differences between Korean and global DALYs were not associated with Korean government research funding.ConclusionsAlthough research funding was associated with the cancer burden in South Korea during the last decade, the distribution of research funds did not appropriately reflect the changes in burden nor the differences between the South Korean and global burden levels. The policy-makers involved in health research budgeting should consider not only the absolute burden values for singular years but also the long-term changes in burden and the country-specific burden when they prioritise public research projects.

Years of life lost as a measure of cancer burden in Colombia, 1997-2012

There is hardly any information regarding years of life lost due to cancer in Colombia. To quantify total and average years of life lost due to cancer in Colombia, and to investigate changes in this burden between 1997 and 2012. We obtained sex-specific data on age distribution, remaining life expectancy, deaths due to specific cancers and total number of deaths from the Colombian Departamento Administrativo Nacional de Estadísticas. We calculated years of life lost based on each individual´s age at death and the remaining life expectancy at that age; as for average years of life, we divided these by the number of deaths due to specific cancers. The total number of cancer deaths increased by 33% between 1997 and 2012, comprising 15% of male and 20% of female deaths in the period 2010-2012. Total years of life lost due to cancer increased by 25.1% for males and 31.1% for females over the study period. The highest increases (>40%) were observed for colorectal, pancreas and kidney cancers in both sexes, for melanomas and bladder cancer in men, and for breast and ovarian cancer in women. Trends in average years of life lost were stable. Almost half (48-50%) of the years of life lost due to childhood cancers were due to leukemia. Cancer is an increasing health burden in Colombia. The high average years of life lost illustrate the poor prognosis of the disease compared to other countries. Primary prevention, early detection, and adequate and timely treatments are needed to change this situation.

Years of life lost as a measure of cancer burden on a national level.

Background:The severity of cancers is often measured in number of deaths. However, number of years of life lost (YLL) may be a more appropriate indicator of impact on society. Here we have calculated the YLL of adult cancers in Norway for the year 2012, as well as for the previous 15-year period.Methods:Data on age composition, expected remaining years of life, total numbers of deaths and deaths due to cancer were retrieved from the National Census Agency Statistics Norway. YLL were calculated for both sexes aged 25–99 years based on each individual's age at death, and the expected remaining years of life at that age.Results:Cancer deaths represented 25.8% of all adult deaths in 2012, with a lower fraction of females (28.7% in men and 23.1% in women), whereas cancer represented 35.2% of all YLL, with a higher fraction of females (32.8% in men and 37.8% in women). Females loose on average more life years to cancer than men (14.9 vs 12.7 years). Average YLL varied from 23.7 (cervical cancer) to 7.9 (prostate cancer). Lung cancer caused almost as many YLL alone (22.1% of cancer-caused YLL) as colon, prostate and breast cancer combined (23.1%). From 1997 to 2012, cancer-caused YLL as a fraction of all YLL increased from 32.5% to 35.2%, but with major differences among diagnoses.Conclusions:Cancer is a major and increasing cause of premature deaths, and YLL may be a more accurate measure than number of deaths. Public health efforts and research funding should be explicitly directed at preventing premature deaths.

A Single Measure of Cancer Burden Combining Incidence with Mortality Rates for Worldwide Application

We attempted to develop an indicator combining incidence and mortality (summary indicator of cancer burden, SMCB) and to compare the magnitudes of cancer burden by world region. The SMCB was used to measure the size of cancer burden summarizing the incidence and mortality. The incidence and mortality were divided in equivalent forms and were split. The criteria dividing the size of cancer burden were used as the maximum incidence and mortality by men and women according to the world database, and the value corresponding to 10% of each maximum was set as the cut-off value. In SMCB, the size of cancer burden was highest for men with lung cancer (SMCB=18) and for women with breast cancer (SMCB=14) in MDR (more developed regions) compared to the size of burden in LDR (lower developed regions) (lung, SMCB=11, breast, SMCB=8). For men, the size of cancer burden by region was highest in EURO (SMCB=18, lung), followed by WPRO (SMCB=16, lung), PAHO (SMCB=14, prostate), AFRO (SMCB=8, prostate) and SEARO (SMCB=7, lung). Moreover, for women, the size of cancer burden was greatest in EURO (SMCB=14, breast), followed by PAHO (SMCB=13, breast), AFRO (SMCB=11, cervix uteri), EMRO (SMCB=9, breast) or SEARO (SMCB=8, cervix uteri) and WPRO (SMCB=7, lung). The summary indicator will help to provide a priority setting for reducing cancer burden in health policy.

Detection of Circulating Tumor Cells of Nonepithelial Origin: A Bench to Bedside Approach

Purpose/Objective(s): No validated biomarkers exist for minimal residual disease (MRD) detection in non-small cell lung cancer (NSCLC). Tumor DNA is continually shed into the circulation, where it can be accessed for analysis by next-generation sequencing (NGS). We aimed to design a NGS-based method for quantifying circulating tumor-derived DNA in NSCLC and other cancers. Materials/Methods: We developed CAPP-Seq (CAncer Personalized Profiling by deep Sequencing), a novel method for noninvasive and sensitive measurement of cancer burden from cfDNA. Our strategy leverages hybrid affinity capture to enrich recurrently mutated genomic regions from tumor genomic DNA and plasma cfDNA. We used mixtures of NSCLC cell line DNA in cfDNA to benchmark CAPP-Seq. We then analyzed a set of NSCLC tumor/normal genomic DNA pairs. Finally, we studied serial plasma samples collected from patients before and after treatment with radiation therapy, chemotherapy, and/or surgery. Results: We show that CAPP-Seq detects multiple types of cancer-specific somatic mutations within NSCLC DNA, including single nucleotide variants, insertions/deletions, and rearrangements. Benchmarking analyses demonstrate that CAPP-Seq accurately enumerates somatic mutations within cfDNA at a fractional abundance of 0.025%. Applying CAPP-Seq to tumor/normal genomic DNA pairs from 11 NSCLC patients uncovered a median of 3 somatic mutations per patient (range, 1-16). Fifteen plasma samples from 7 patients were profiled by CAPP-Seq. The abundance of patient-specific cancer markers within plasma cfDNA was readily measured by CAPP-Seq in both earlyand late-stage NSCLC. Importantly, circulating tumor DNA responded appropriately to anti-cancer therapies, becoming undetectable in 2 patients (after surgery and chemoradiation therapy, respectively) and declining but remaining detectable in 5 patients (after chemotherapy in 4 patients and surgery in 1 patient). CAPP-Seq measurements correlated with tumor volume (R Z 0.97) and allowed for the detection of resistance mutations in patients being treated with targeted therapies. Conclusions: In this study, we described CAPP-Seq, a novel NGS-based approach to MRD testing in cancer patients. CAPP-Seq could have clinical utility for monitoring disease burden and response to therapy, early detection of relapse, distinguishing radiation pneumonitis from relapse, and risk stratification in early-stage NSCLC following surgery or stereotactic body radiation therapy. Ultimately, we envision CAPP-Seq becoming a routine clinical assay for measuring tumor burden in diverse cancers from plasma and other body fluids. Author Disclosure: S.V. Bratman: None. A.M. Newman: None. J. To: None. J.F. Wynne: None. J.W. Neal: None. H. Wakelee: None. J. Shrager: None. B.W. Loo: None. A.A. Alizadeh: None. M. Diehn: None.

A Resource Allocation Metric for Thyroid Biopsies

The aim of this study was to assess the adequacy of departmental resource allocation to ultrasound-guided biopsies of the thyroid gland. The numbers of image-guided breast, prostate, and thyroid biopsies performed in the authors' radiology department over a 12-month period in 2009 were determined. The predicted deaths in Canada from breast, prostate, and thyroid cancer over the same period were obtained from the Canadian Cancer Society. The number of biopsies performed on each organ was divided by the expected mortality from the respective cancer. Approximately 2,400 breast biopsies, 910 prostate biopsies, and 610 thyroid biopsies were performed. Using mortality as a measure of cancer burden, the biopsy/cancer burden ratio for thyroid cancer was 7 times that for breast cancer and 15 times that for prostate cancer. The skewed ratio in favor of thyroid biopsies supports concerns that current trends in the investigation of thyroid nodules may represent an overconsumption of health resources.

Years of life lost (YLL) from cancer is an important measure of population burden — and should be considered when allocating research funds

Recently, cancer mortality has been compared to research spending by the National Cancer Research Institute (NCRI), whose research budget is approximately £250 million. The analysis shows a mis-match between mortality and research spending. As well as crude mortality rates, other measures of cancer burden should be considered because they contribute additional information. ‘Years of life lost’ (YLL) summed over each individual dying after a diagnosis of cancer represents a population-based mortality indicator of the impact of that disease on society. Years of life lost divided by the number of deaths for each cancer site produces an additional statistic, the average years of life lost (AYLL), which is a measure of the burden of cancer to the individual patient. For 17 cancer sites where data are available, four tumour sites have a rather large difference in mortality, comparing YLL to crude mortality. Years of life lost shows the population burden from cancers of the ovary, cervix, and CNS to be rather larger than suggested by crude mortality, despite screening programmes for cervix cancer. Using YLL, the underprovision of funding for lung cancer research is similar to that reported using percentage mortality. Breast cancer and leukaemia receive a relatively higher research spend than the population burden of these cancers, and the spending on leukaemia is quite extreme. Prostate cancer has a low per cent YLL but attracts a moderate amount of research spending. The use of AYLL as an indicator of individual cancer burden considerably changes the ranking of the mortality from different tumours. The mean AYLL is 12.5 years. Prostate cancer has the lowest AYLL, only 6.1 years; brain tumour patients have the highest, at just over 20 years. Comparing AYLL to research spending suggests four ‘Cinderella’ cancer sites with high individual cancer burden but low research spending: CNS tumours, cervix and kidney cancers, and melanoma. Breast cancer and leukaemia have roughly average AYLL but a considerable excess of research spending. YLL emphasises the discrepancy between research spending and mortality, and may be helpful for decisions concerning research support. Avearage years of life lost measures the burden to individual patients and may be helpful where individuals’ needs are relevant, such as palliative care. As well as crude mortality, more subtle and comprehensive calculations of mortality statistics would be useful in debates on research funding and public health issues.

Cancer burden in the year 2000. The global picture

Although the general idea of ‘burden’ of a disease to a community seems fairly straightforward, there are multiple dimensions in which it may be expressed, either in terms of disease frequency (the ‘need’ for services) or the demand which it places upon them. In this review, we confine ourselves to three elementary measures of cancer frequency: incidence, mortality and prevalence. Incidence is the number of new cases occurring. It can be expressed as an absolute number of cases per year (the volume of new patients presenting for treatment) or as a rate per 100 000 persons per year. The latter provides an approximation to the average risk of developing a cancer, and is necessary if we wish to compare the risk of disease between populations (countries, ethnic groups, or different time periods within a country, for example). When considering the impact of primary prevention strategies, a reduction in incidence (occurrence of new cases) is the appropriate statistic to use. Mortality is the number of deaths occurring, and the mortality rate the number of deaths per 100 000 persons per year. The number of deaths provides one measure (and a rather unambiguous one) of the outcome or impact of cancer. It is the product of the incidence and the fatality of a given cancer. Fatality, the inverse of survival, is the proportion of cancer cases that die and this is generally assumed to be the most severe sequel of the disease. Mortality rates therefore measure the average risk to the population of dying from a specific cancer, while fatality (1-survival) represents the probability that an individual with cancer will die from it. Mortality rates are sometimes used as a convenient proxy measure of the risk of acquiring the disease (incidence) when comparing different groups, since they may be more generally available (as described below). However, when used in this way, an assumption of equal survival/fatality in the populations being compared is introduced. Since this is rarely correct—there are, for example, quite large differences between countries—it is safer to use mortality as a measure of outcome rather than occurrence. Prevalence: There is no agreed definition of ‘prevalence’ of cancer. Strictly speaking, it is the number of persons in a defined population alive at a given time who have had cancer diagnosed at some time in the past. However, the resource requirements for treating newly diagnosed patients are very different from those for supporting long-term survivors. Thus, overall prevalence is not particularly useful for healthcare planning purposes, especially as a large proportion of long-term survivors can be considered cured. Partial prevalence, which limits the number of patients to those diagnosed during a fixed time in the past, is therefore a more useful measure of cancer burden. Prevalence for cases diagnosed within 1, 3 and 5 years are likely to be of relevance to the different stages of cancer therapy, namely, initial treatment (1 year), clinical follow-up (3 years) and cure (5 years). Patients who are still alive 5 years after diagnosis are usually considered cured since the death rates of such patients are similar to those in the general population. There are some exceptions, primarily that of female breast cancer, for which the risk of death remains higher than the general population for many more years. Several other more complex statistics have been used to measure the impact of disease, particularly in health economics. They include person-years of life lost (how many years of normal lifespan are lost due to deaths from cancer). This measurement may be refined by giving different values to life-years at different ages, so that a year saved at, for example, age 20 years, is valued

Are Increasing 5-Year Survival Rates Evidence of Success Against Cancer?

Increased 5-year survival for cancer patients is generally inferred to mean that cancer treatment has improved and that fewer patients die of cancer. Increased 5-year survival, however, may also reflect changes in diagnosis: finding more people with early-stage cancer, including some who would never have become symptomatic from their cancer. To determine the relationship over time between 5-year cancer survival and 2 other measures of cancer burden, mortality and incidence. Using population-based statistics reported by the National Cancer Institute Surveillance, Epidemiology, and End Results Program, we calculated the change in 5-year survival from 1950 to 1995 for the 20 most common solid tumor types. Using the tumor as the unit of analysis, we correlated changes in 5-year survival with changes in mortality and incidence. The association between changes in 5-year survival and changes in mortality and incidence measured using simple correlation coefficients (Pearson and Spearman). From 1950 to 1995, there was an increase in 5-year survival for each of the 20 tumor types. The absolute increase in 5-year survival ranged from 3% (pancreatic cancer) to 50% (prostate cancer). During the same period, mortality rates declined for 12 types of cancer and increased for the remaining 8 types. There was little correlation between the change in 5-year survival for a specific tumor and the change in tumor-related mortality (Pearson r=.00; Spearman r=-.07). On the other hand, the change in 5-year survival was positively correlated with the change in the tumor incidence rate (Pearson r=+. 49; Spearman r=+.37). Although 5-year survival is a valid measure for comparing cancer therapies in a randomized trial, our analysis shows that changes in 5-year survival over time bear little relationship to changes in cancer mortality. Instead, they appear primarily related to changing patterns of diagnosis. JAMA. 2000.

Annual cancer incidence rates for Hispanics in the United States: surveillance, epidemiology, and end results, 1992-1996.

The expansion of the Surveillance, Epidemiology, and End Results (SEER) program and the determination of annual population estimates by county level for different racial/ethnic groups since 1990 allow the calculation of annual cancer incidence rates for Hispanics. Incidence rates were calculated for 11 SEER areas representing 25% of the Hispanic population. Standard regression analyses of log-transformed rates were used to determine the trends of the rates. An important measure of the cancer burden among Hispanics is the rank order of their cancers. For Hispanic males, the five major cancers (in declining order) are prostate, lung and bronchus, colon/rectum, non-Hodgkin lymphoma, and stomach cancers. For Hispanic females, the top five cancers are breast, colon/rectum, lung and bronchus, cervix, and endometrial cancers. Another measure of cancer burden is their rates relative to white non-Hispanics. Hispanic males have rates greater than white non-Hispanic males for stomach (1.6 times greater) and liver and IBD cancers (2.2), whereas Hispanic females have greater rates for cervix (2.2 times greater), liver and IBD (2.0), stomach (2.1), and gallbladder cancers (3.3). Other measures of cancer burden include the trends in Hispanic rates. Hispanic males have significant declining trends for all sites, prostate cancer, and urinary bladder cancer, and an increasing trend for liver and IBD cancers. Hispanic females have significant declining trends for cervix and urinary bladder cancers. The SEER cancer incidence rates and trends provide a general overview of the cancer burden among Hispanics residing in the SEER sites. This type of information is critical for determining interventions to reduce the cancer burden among Hispanics in the United States.