Treatment and Outcomes of Non-Small-Cell Lung Cancer Patients with High Comorbidity

Background: The life expectancy of untreated non-small-cell lung cancer (NSCLC) is dismal, while treatment for NSCLC improves survival. The presence of comorbidities is thought to play a significant role in the decision to treat or not treat a given patient. We aim to evaluate the association of comorbidities with the survival of patients treated for NSCLC. Methods: We performed a retrospective study of patients aged ≥66 years with invasive NSCLC between the years 2007 and 2011 in the Surveillance, Epidemiology, and End Results Kentucky Cancer Registry. Comorbidity was measured using the Klabunde Comorbidity Index (KCI), and univariate and multivariate logistic regression models were used to measure association between receiving treatment and comorbidity. Kaplan-Meier plots were constructed to estimate time-to-event outcomes. Results: A total of 4014 patients were identified; of this, 94.9% were white and 55.7% were male. The proportion of patients who did not receive any treatment was 8.7%, 3.9%, 19.1%, and 23.5% for stages I, II, III, and IV, respectively (p \u3c 0.0001). In multivariate analysis, older age, higher stage, and higher comorbidity (KCI ≥ 3) were associated with a lower likelihood of receiving any treatment. The median overall survival (OS) for untreated and KCI=0 was 17.7 months for stages I and II, 2.3 months for stage III, and 1.3 months for stage IV. The median OS for treated and KCI=0 was 58.9 months for stages I and II, 16.8 months for stage III, and 5.8 months for stage IV (p \u3c 0.01). Treatment was an independent predictor of OS in multivariate analysis that included KCI scores. Conclusion: Our data suggest that lung cancer patients may derive a survival benefit from therapies, regardless of the presence of comorbidities, although the degree of benefit seems to decrease with higher KCI scores

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Intensity modulated radiation therapy following lumpectomy in early-stage breast cancer: Patterns of use and cost consequences among Medicare beneficiaries.

PURPOSE:In 2013, the American Society for Radiation Oncology (ASTRO) issued a Choosing Wisely recommendation against the routine use of intensity modulated radiotherapy (IMRT) for whole breast irradiation. We evaluated IMRT use and subsequent impact on Medicare expenditure in the period immediately preceding this recommendation to provide a baseline measure of IMRT use and associated cost consequences. METHODS AND MATERIALS:SEER records for women ≥66 years with first primary diagnosis of Stage I/II breast cancer (2008-2011) were linked with Medicare claims (2007-2012). Eligibility criteria included lumpectomy within 6 months of diagnosis and radiotherapy within 6 months of lumpectomy. We evaluated IMRT versus conventional radiotherapy (cRT) use overall and by SEER registry (12 sites). We used generalized estimating equations logit models to explore adjusted odds ratios (OR) for associations between clinical, sociodemographic, and health services characteristics and IMRT use. Mean costs were calculated from Medicare allowable costs in the year after diagnosis. RESULTS:Among 13,037 women, mean age was 74.4, 50.5% had left-sided breast cancer, and 19.8% received IMRT. IMRT use varied from 0% to 52% across SEER registries. In multivariable analysis, left-sided breast cancer (OR 1.75), living in a big metropolitan area (OR 2.39), living in a census tract with ≤$90,000 median income (OR 1.75), neutral or favorable local coverage determination (OR 3.86, 1.72, respectively), and free-standing treatment facility (OR 3.49) were associated with receipt of IMRT (p<0.001). Mean expenditure in the year after diagnosis was$8,499 greater (p<0.001) among women receiving IMRT versus cRT. CONCLUSION:We found highly variable use of IMRT and higher expenditure in the year after diagnosis among women treated with IMRT (vs. cRT) with early-stage breast cancer and Medicare insurance. Our findings suggest a considerable opportunity to reduce treatment variation and cost of care while improving alignment between practice and clinical guidelines

Long term follow-up of neoadjuvant chemotherapy for non-small cell lung cancer (NSCLC) investigating early positron emission tomography (PET) scan as a predictor of outcome

Abstract Background Neoadjuvant chemotherapy is effective in improving survival of resectable NSCLC. Based on findings in the adjuvant and metastatic setting, FDG positron emission tomography (PET) scans may offer early prognostic or predictive value after one cycle of induction chemotherapy. Methods In this phase II non-randomized trial, patients with AJCC version 6 stage IB to IIIB operable NSCLC were treated with 3 cycles of cisplatin and pemetrexed neoadjuvant chemotherapy. Patients underwent FDG-PET scanning prior to and 18 to 21 days after the first cycle of chemotherapy. Investigators caring for patients were blinded to results, unless the scans showed evidence of disease progression. FDG-PET response was defined prospectively as a ≥ 20% decrease in the SUV of the primary lesion. Results Between October 2005 and February 2010, 25 patients enrolled. Fifty two percent were female, 88% white, and median age was 62 years. Histology was divided into adenocarcinoma 66%, not otherwise specified (NOS) 16%, squamous cell 12%, and large cell 4%. Stage distribution was: 16% IB, 4% IIB, and 79% IIIA. Treatment was well tolerated and only one patient had a grade 4 toxicity. The median follow up was 95 months. The 5 year progression free survival (PFS) and overall survival (OS) for the entire population were 54 and 67%, respectively. Eighteen patients had a baseline FDG-PET scan and a repeat scan at day 18–21 available for comparison. Ten patients (56%) were considered metabolic responders on the day 18–21 FDG-PET scan. Responders had a 5 year PFS and OS of 60 and 70%, respectively, while the percentage for non-responders was 63 and 75% (p = 0.96 and 0.85). Conclusions This phase II trial did not demonstrate that a PET scan after one cycle of chemotherapy can predict survival outcomes of patients with NSCLC treated with neoadjuvant chemotherapy. Trial registration NCT00227539 registered September 28th, 2005