A hybrid model for reducing ecological bias

Influence of timeliness and receipt of first treatment on geographic variation in non-small cell lung cancer mortality

Mortality from non-small cell lung cancer (NSCLC) exhibits substantial geographical disparities. However, there is little evidence on whether this variation could be attributed to patients' clinical characteristics and/or socioeconomic inequalities. This study evaluated the independent and relative contribution of the individual- and area-level risk factors on geographic variation in 2-year all-cause mortality among NSCLC patients. In the Hierarchical-related regression approach, we used the Bayesian spatial multilevel logistic regression model to combine individual- and area-level predictors with outcomes while accounting for geographically structured and unstructured correlation. Individual-level data included 3330 NSCLC cases reported to the Victoria Lung Cancer Registry between 2011 and 2016. Area-level data comprised socioeconomic disadvantage, remoteness and pollution data at the postal area level in Victoria, Australia. With the inclusion of significant individual- and area-level risk factors, timely (≤14 days) first definitive treatment (odds ratio [OR] = 0.73, 95% credible interval [Crl] = 0.56-0.94) and multidisciplinary meetings (MDM) (OR = 0.74, 95% Crl = 0.59-0.93) showed an independent association with a lower likelihood of NSCLC 2-year all-cause mortality. Timely and delayed (>14 days) first nondefinitive treatment, no treatment, advanced clinical stage, smoking, poor performance status, public hospital insurance and area-level deprivation were independently associated with a higher likelihood of 2- and 5-year all-cause mortality. NSCLC's 2-year all-cause mortality exhibited substantial geographic variation, mainly associated with timeliness and receipt of first definitive treatment, no treatment followed by patient prognostic factors with some contribution from area-level deprivation, MDM and public hospital insurance. This study highlights NSCLC patients should receive the first definitive treatment within the recommended 14-days from diagnosis.

Association between Receipt of Guideline-Concordant Lung Cancer Treatment and Individual- and Area-Level Factors: A Spatio-Temporal Analysis

BACKGROUND

Guideline-concordant treatment (GCT) of lung cancer has been observed to vary across geographic regions over the years. However, there is little evidence as to what extent this variation is explained by differences in patients' clinical characteristics versus contextual factors, including socioeconomic inequalities.

METHODS

This study evaluated the independent effects of individual- and area-level risk factors on geographic and temporal variation in receipt of GCT among patients with lung cancer. Receipt of GCT was defined on the basis of the National Comprehensive Cancer Network guidelines. We used Bayesian spatial-temporal multilevel models to combine individual and areal predictors and outcomes while accounting for geographically structured and unstructured correlation and linear and nonlinear trends.

RESULTS

Our study included 4,854 non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC) cases, reported to the Victorian Lung Cancer Registry between 2011 and 2018. Area-level data comprised socioeconomic disadvantage and remoteness data at the local government area level in Victoria, Australia. Around 60.36% of patients received GCT, and the rates varied across geographic areas over time. This variation was mainly associated with poor performance status, advanced clinical stages, NSCLC types, public hospital insurance, area-level deprivation, and comorbidities.

CONCLUSIONS

This study highlights the need to address disparities in receipt of GCT among patients with lung cancer with poor performance status, NSCLC, advanced clinical stage, stage I-III SCLC, stage III NSCLC, public hospital insurance, and comorbidities, and living in socioeconomically disadvantaged areas.

IMPACT

Two-year mortality outcomes significantly improved with GCT. Interventions aimed at reducing these inequalities could help to improve lung cancer outcomes.

Combining individual and aggregated data to investigate the role of socioeconomic disparities on cancer burden in Italy

Quantifying socioeconomic disparities and understanding the roots of inequalities are growing topics in cancer research. However, socioeconomic differences are challenging to investigate mainly due to the lack of accurate data at individual-level, while aggregate indicators are only partially informative. We implemented a multiple imputation algorithm within a statistical matching framework that combines diverse sources of data to estimate individual-level associations between income and risk of breast and lung cancer, adjusting for potential confounding factors in Italy. The framework is computationally flexible and can be adapted to similar contexts.

Lung cancer mortality and radon concentration in a chronically exposed neighborhood in Chihuahua, Mexico: a geospatial analysis

This study correlated lung cancer (LC) mortality with statistical data obtained from government public databases. In order to asses a relationship between LC deaths and radon accumulation in dwellings, indoor radon concentrations were measured with passive detectors randomly distributed in Chihuahua City. Kriging (K) and Inverse-Distance Weighting (IDW) spatial interpolations were carried out. Deaths were georeferenced and Moran's I correlation coefficients were calculated. The mean values (over n = 171) of the interpolation of radon concentrations of deceased's dwellings were 247.8 and 217.1 Bq/m³, for K and IDW, respectively. Through the Moran's I values obtained, correspondingly equal to 0.56 and 0.61, it was evident that LC mortality was directly associated with locations with high levels of radon, considering a stable population for more than 25 years, suggesting spatial clustering of LC deaths due to indoor radon concentrations.

Colon and rectal cancer incidence and water trihalomethane concentrations in New South Wales, Australia

Background

There is evidence, although inconsistent, that long term exposure to disinfection by products (DBPs) increases the risk of bowel cancer. No study has been conducted in Australia to examine this association and due to difference in the methods of disinfection the risk can vary across geographical regions and. This study was conducted to analyse the association of trihalomethanes (THMs) in water with colon and rectal cancer in NSW Australia.

Methods

Average yearly concentrations of total and individual species of THMs were obtained for 50 local government areas (LGAs). Indirectly-standardized incidence rates of colon and rectal cancers in LGAs for the period 1995 to 2001 were regressed against mean THM concentrations lagged five years, adjusting for socioeconomic status, high risk drinking, smoking status, usual source of water and year of diagnosis, including local and global random effects within a Bayesian framework. The incidence rate ratios (IRRs) for an interquartile range (IQR) increase in THMs were estimated.

Results

Using five year lag of exposure there was a positive association between bromoform concentration and CRC in men (IRR = 1.025, 95% CI 1.010, 1.040) but not in women (IRR = 1.003, 95% CI 0.987, 1.018). The association in men was mainly found in colon cancer with bromoform (IRR = 1.035, 95% CI 1.017, 1.053). There was no appreciable association of colorectal cancer with other species of THMs. Sensitivity analyses did not materially change the associations observed.

Conclusion

A positive association was observed between colon cancer and water bromoform concentrations in men. Given the potential population impact of such an association, further research into the relationship between THMs, particularly brominated species, and colorectal cancer is warranted.

Incorporating spatial variability within epidemiological studies of environmental exposures

Recently there has been great interest in modelling the association between aggregate disease counts and environmental exposures measured at point locations, for example via air pollution monitors. In such cases, the standard approach is to average the observed measurements from the individual monitors and use this in a log-linear health model. Hence such studies are ecological in nature being based on spatially aggregated health and exposure data. Here we investigate the potential for biases in the estimates of the effects on health in such settings. Such ecological bias may occur if a simple summary measure, such as a daily mean, is not a suitable summary of a spatially variable pollution surface. We assess the performance of commonly used models when confronted with such issues using simulation studies and compare their performance with a model specifically designed to acknowledge the effects of exposure aggregation. In addition to simulation studies, we apply the models to a case study of the short-term effects of particulate matter on respiratory mortality using data from Greater London for the period 2002-2005.

On ecological studies: a short communication

The typical objective of research is to try and identify cause-and-effect relationships. As with any research design, there are strengths and weaknesses involved in trying to achieve this objective. Some study designs are stronger than others in attempting to establish cause-and-effect associations. The task of establishing cause-and-effect relationships is challenging (Hill, 1965) and any study that does not include experimentation, that is by manipulating a variable's exposure, is inhibited from drawing causal inferences (Heath, 1995). Similarly, statistical significance is also based on probability rather than certainty. This article focuses on a particular research design, namely, the ecological study, and attempts to serve as a reminder that the design has its place in the realm of various research designs.