Misclassification of the actual causes of death and its impact on analysis: A case study in non-small cell lung cancer

Causes of Death in Nonmalignant Meningioma

OBJECTIVES

Nonmalignant meningioma (NM) is the most common brain tumor in the United States (U.S.), accounting for 54% of nonmalignant brain tumors. This study aims to investigate the causes of death in NM patients and their possible associations with demographic factors.

METHODS

Using the Surveillance, Epidemiology, and End Results (SEER) database, we analyzed 116,430 NM patients diagnosed between the years 2004 and 2018.

RESULTS

A total of 31,640 deaths were observed. Non-tumor diseases accounted for 63.9% of all deaths. Out of these non-tumor deaths, we found that the most common causes were heart disease (18.7% of deaths), cerebrovascular disease (7.4% of deaths), and Alzheimer disease (4.5% of deaths). On the other hand, cancer was responsible for 27.4% of deaths, while in situ and benign tumor deaths accounted for only 8.7%.

CONCLUSIONS

This is the first U.S. population-based study to investigate the causes of death in NM patients. We found that non-tumor diseases accounted for the majority of deaths. The risks of mortality caused by heart disease, cerebrovascular disease, diabetes, and Alzheimer disease were significantly elevated. These data can help improve survival outcomes for NM patients, particularly if adjusted by demographic risk factors.

Associations of Change in Body Size With All-Cause and Cause-Specific Mortality Among Healthy Older Adults

Importance

The association between weight change and subsequent cause-specific mortality among older adults is not well described. The significance of changes in waist circumference (WC) has also not been compared with weight change for this purpose.

Objective

To examine the associations of changes in body weight and WC with all-cause and cause-specific mortality.

Design, Setting, and Participants

This cohort study is a post hoc analysis of data from the Aspirin in Reducing Events in the Elderly (ASPREE) randomized clinical trial, which recruited participants between March 1, 2010, and December 31, 2014. The study included community-based older adults (16 703 Australian participants aged ≥70 years and 2411 US participants aged ≥65 years) without evident cardiovascular disease (CVD), dementia, physical disability, or life-limiting chronic illness. Data analysis was performed from April to September 2022.

Exposures

Body weight and WC were measured at baseline and at annual visit 2. Analysis models were adjusted for baseline body mass index because height and weight were measured at baseline, allowing for calculation of body mass index and other variables. Both body weight and WC changes were categorized as change within 5% (stable), decrease by 5% to 10%, decrease by more than 10%, increase by 5% to 10%, and increase by more than 10%.

Main Outcomes and Measures

All-cause, cancer-specific, CVD-specific, and noncancer non-CVD-specific mortality. Mortality events were adjudicated by an expert review panel. Cox proportional hazards regression and competing risk analyses were used to calculate hazard ratios (HRs) and 95% CIs.

Results

Among 16 523 participants (mean [SD] age, 75.0 [4.3] years; 9193 women [55.6%]), 1256 deaths were observed over a mean (SD) of 4.4 (1.7) years. Compared with men with stable weight, those with a 5% to 10% weight loss had a 33% higher (HR, 1.33; 95% CI, 1.07-1.66) risk of all-cause mortality, and those with more than a 10% decrease in body weight had a 289% higher (HR, 3.89; 95% CI, 2.93-5.18) risk. Compared with women with stable weight, those with a 5% to 10% weight loss had a 26% higher (HR, 1.26; 95% CI, 1.00-1.60) risk of all-cause mortality, and those with more than a 10% decrease in body weight had a 114% higher (HR, 2.14; 95% CI, 1.58-2.91) risk. Weight loss was associated with a higher cancer-specific mortality (>10% decrease among men: HR, 3.49; 95% CI, 2.26-5.40; 5%-10% decrease among women: HR, 1.44; 95% CI, 1.46-2.04; >10% decrease among women: HR, 2.78; 95% CI, 1.82-4.26), CVD-specific mortality (>10% decrease among men: HR, 3.14; 95% CI, 1.63-6.04; >10% decrease among women: HR, 1.92; 95% CI, 1.05-3.51), and noncancer non-CVD-specific mortality (>10% decrease among men: HR, 4.98; 95% CI, 3.14-7.91). A decrease in WC was also associated with mortality.

Conclusions and Relevance

This cohort study of healthy older adults suggests that weight loss was associated with an increase in all-cause and cause-specific mortality, including an increased risk of cancer, CVD, and other life-limiting conditions. Physicians should be aware of the significance of weight loss, especially among older men.

Association between trends of mortality and incidence, survival and stage at diagnosis for six digestive and respiratory cancers in United States (2009-2013)

BACKGROUND

A decrease in cancer mortality has been reported in the USA, possibly due to decreased incidence, downstaging and improved survival. The aim of the present study is to estimate the contribution of these factors on the trend in cancer mortality.

METHODS

Data on incidence, mortality, stage at diagnosis, and overall and stage-specific survival for six common digestive and respiratory cancers (esophagus, stomach, colorectal, liver, pancreas and lung) during 2009-2013 in the USA from the surveillance, epidemiology and end results (SEER) program, was analyzed using generalized linear models separately among men and women.

RESULTS

Our study showed a decrease in mortality for esophageal (-0.09/100 000/year and -0.03/100 000/year), stomach (-0.11/100 000/year and -0.05/100 000/year), colorectal (-0.45/100 000/year and -0.29/100 000/year) and lung cancer (-1.89/100 000/year in men and -0.78/100 000/year in women) in men and women, respectively: for all of them, except lung cancer in women, there was a decrease in the incidence of comparable or greater magnitude; stage distribution and survival also contributed to the decrease in mortality for lung and colorectal cancer. Mortality from pancreatic cancer was stable: an increase in incidence was counterbalanced by an improvement in survival. Mortality from liver cancer increased, driven by an increase in mortality that was not offset by favorable trends in stage distribution and survival.

CONCLUSIONS

Trends in mortality were primarily affected by changes in incidence; an increase in the proportion of local stage at diagnosis and improved survival, although evident for some cancers, played a lesser role in mortality trends.

Has the cancer-related death trend been changing in Turkey? An evaluation of the period between 2009 and 2019

BACKGROUND

The objective of this study was to determine the trend of cancer-related death rates between 2009 and 2019 in Turkey for all cancers combined and the five cancer types with the highest mortality: lung, stomach, pancreas, breast, and colon cancers.

METHODS

Cancer mortality data were obtained from the Turkish Statistical Institute (TURKSTAT) and standardized by age using the World Health Organization (WHO) standard population ratios. The change in cancer-related mortality over the years was evaluated using Joinpoint Regression Analysis (JRA).

RESULTS

Total cancer-related deaths increased by 2.2% annually between 2009 and 2014 and decreased by 2.9% annually between 2014 and 2019 (p < 0.05). Among men; lung cancer-related deaths increased by 2.4% annually between 2009 and 2014 and decreased by 3.4% annually between 2014 and 2019 (p < 0.05), stomach cancer-related deaths decreased by 5.1% annually between 2014 and 2019 (p < 0.05), colon cancer-related deaths increased by 5.8% annually between 2009 and 2015 and decreased by 3.3% annually between 2015 and 2019 (p < 0.05), pancreatic cancer-related deaths increased annually by 5.6% in 2009-2013 (p < 0.05). Among women; lung cancer-related deaths increased by 2.5% annually between 2009 and 2016 (p < 0.05), stomach cancer-related deaths increased annually by 2.3% between 2009 and 2014 and decreased annually by 4.5% between 2014 and 2019 (p < 0.05), colon cancer-related deaths increased by 2.5% annually between 2009 and 2017 (p < 0.05), pancreatic cancer-related deaths increased by 7.4% annually between 2009 and 2013 (p < 0.05) and breast cancer-related deaths increased by 2.2% annually between 2009 and 2019 (p < 0.05).

CONCLUSION

Mortality data in Turkey are collected only by TURKSTAT, which raises concern regarding the incompletion of the data. While this might lead to underestimation, the trend shows that there has been a decrease in total cancer-related deaths in Turkey. Pancreatic cancer, on the other hand, gains a higher proportion in cancer-related deaths in Turkey as in the world. Increasing deaths from lung and breast cancer in women remind of the importance of tobacco control interventions and cancer screening programs.

Prognostic Value of Computed Tomography-Derived Fractional Flow Reserve Comparison With Myocardial Perfusion Imaging

OBJECTIVES

The aim of this study was to compare the incremental prognostic value of coronary computed tomography (CT) angiography (CCTA)-derived machine learning fractional flow reserve CT (ML-FFRct) versus that of ischemia detected on single-photon emission-computed tomography (SPECT) myocardial perfusion imaging (MPI) on incident cardiovascular outcomes.

BACKGROUND

SPECT MPI and ML-FFRct are noninvasive tools that can assess the hemodynamic significance of coronary atherosclerotic disease.

METHODS

We studied a retrospective cohort of consecutive patients who underwent clinically indicated CCTA and SPECT MPI. ML-FFRct was computed using a ML prototype. The primary outcome was all-cause mortality and nonfatal myocardial infarction (D/MI), and the secondary outcome was D/MI and unplanned revascularization, percutaneous coronary intervention (PCI) or coronary artery bypass graft (CABG) occurring more than 90 days postimaging. Multiple nested multivariate cox regression was used to model a scenario wherein an initial anatomical assessment was followed by a functional assessment.

RESULTS

A total of 471 patients (mean age: 64 ± 13 year; 53% males) were included. Comorbidities were prevalent (78% hypertension, 66% diabetes, 81% dyslipidemia). ML-FFRct was <0.8 in at least 1 proximal/midsegment was present in 41.6% of patients, and ischemia on MPI was present in 13.8%. After a median follow-up of 18 months, 7% of patients (n = 33) experienced D/MI. On multivariate Cox proportional analysis, the presence of ischemia on MPI but not ML-FFRct significantly predicted D/MI (HR: 2.3; 95% CI: 1.0-5.0; P = 0.047; or HR: 0.7; 95% CI: 0.3-1.4; P = 0.306 respectively) when added to CCTA obstructive stenosis. Furthermore, the model with SPECT ischemia had higher global chi-square result and significantly improved reclassification. Results were similar using the secondary outcome and on several sensitivity analyses.

CONCLUSIONS

In a high-risk patient cohort, SPECT MPI but not ML-FFRct adds independent and incremental prognostic information to CCTA-based anatomical assessment and clinical risk factors in predicting incident outcomes.

Optimal resection rate for lung cancer in the UK: how high should we go?

Background

The optimal resection rate for institutions managing early-stage primary lung cancer is not known. Whether the prognosis of patients who do not proceed to operation is determined by their comorbidities for which they were deemed at prohibitively high-operative risk, or disease progression, is uncertain. We investigated the outcomes of patients with early-stage lung cancer who were considered for surgical management.

Methods

We reviewed the outcomes of consecutive patients who were considered for resection of early-stage primary lung cancer at Oxford University Hospitals National Health Service Foundation Trust between 2012 and 2017.

Results

Between 29 November 2012 and 31 March 2017, 467 consecutive patients underwent resection with curative intent for primary lung cancer (operative group), while 81 patients were deemed resectable but either inoperable or did not wish to proceed to operation (non-operative group). Reason for not proceeding to resection was cardiovascular in 16 patients (19.8%), respiratory in 21 (25.9%), cardiorespiratory in 11 (13.6%), performance status in 8 (9.9%) and patient choice in 25 (30.9%) patients. Sixty-six patients (81.5%) received an alternative radical treatment. Median follow-up was 169 weeks (IQR 119–246 weeks) in the operative group and 118 weeks (IQR 74–167 weeks) in the non-operative group. Median survival of patients with early-stage lung cancer who did not proceed to operation was 2.5 years; median survival of patients undergoing lung cancer resection was undefined (p<0.0001). Lung cancer was documented as directly or indirectly leading to or contributing to death in 40 patients (76.9%). In 11 patients, the cause of death was due to comorbidities (21.2%).

Conclusions

Patients turned down for operation in a high-resection rate UK unit have limited survival due to lung cancer progression. We conclude that ‘optimal’ resection rates may not have been reached in the UK even in high-resection rate centres.

Cause of death for patients with breast cancer: discordance between death certificates and medical files, and impact on survival estimates

BACKGROUND

Registration and coding of cause of death is prone to error since determining the exact underlying condition leading directly to death is challenging. In this study, causes of death from the death certificates were compared to patients' medical files interpreted by experts at University Hospitals Leuven (UHL), to assess concordance between sources and its impact on cancer survival assessment.

METHODS

Breast cancer patients treated at UHL (2009-2014) (follow-up until December 31st 2016) were included in this study. Cause of death was obtained from death certificates and expert-reviewed medical files at UHL. Agreement was calculated using Cohen's kappa coefficient. Cause-specific survival (CSS) was calculated using the Kaplan-Meier method and the relative survival probability (RS) using the Ederer II and Pohar Perme method.

RESULTS

A total of 2862 patients, of whom 354 died, were included. We found an agreement of 84.7% (kappa-value of 0.69 (95% C.I.: 0.62-0.77)) between death certificates and medical files. Death certificates had 10.7% false positive and 4.5% false negative rates. However, five-year CSS and RS measures were comparable for both sources.

CONCLUSION

For breast cancer patients included in our study, fair agreement of cause of death was seen between death certificates and medical files with similar CSS and RS estimations.

Reporting net survival in populations: a sensitivity analysis in lung cancer demonstrates the differential implications of reporting relative survival and cause-specific survival

Background

Net survival is commonly quantified as relative survival (observed survival among lung cancer patients versus expected survival among the general population) and cause-specific survival (lung cancer–specific survival among lung cancer patients). These approaches have drastically different assumptions; hence, failure to distinguish between them results in significant implications for study findings. We quantified the differences between relative and cause-specific survival when reporting net survival of patients with non-small cell lung cancer (NSCLC).

Methods

Cases of NSCLC diagnosed between 2004 and 2014 were extracted from the Surveillance, Epidemiology, and End Results database. The net survival of each stage-by-age stratum was expressed as cause-specific survival (Kaplan-Meier approach) and relative survival (Ederer II approach); percentage-point (pp) differences between the survival estimates were quantified up to 10 years postdiagnosis.

Results

Analyses included 263,894 cases. Cause-specific survival estimates were higher than relative survival estimates across all strata. Although the differences were negligible at 1 year postdiagnosis, they increased with increasing years of follow-up, up to 9.3 pp at 10 years (eg, aged 60–74 with stage I disease: 53.0% vs 43.7%). Differences in survival estimates between the methods also increased by increasing age groups (eg, at 10 years postdiagnosis: 5.1 pp for ages 18–44, 8.8 pp for ages 45–59, and 9.3 pp for ages 60–74) but decreased drastically for those aged ≥75 (3.1 pp).

Conclusion

Relative survival and cause-specific survival are not interchangeable. The type of survival estimate used in cancer studies should be specified, particularly for long-term survival.