Impact of Residential Concentration of PM2.5 Analyzed as Time-Varying Covariate on the Survival Rate of Lung Cancer Patients: A 15-Year Hospital-Based Study in Upper Northern Thailand

Abstract

Air pollutants, especially particulate matter (PM) ≤ 2.5 µm (PM2.5) and PM ≤ 10 µm (PM10), are a major concern in upper northern Thailand. Data from a retrospective cohort comprising 9820 lung cancer patients diagnosed from 2003 to 2018 were obtained from the Chiang Mai Cancer Registry, and used to evaluate mortality and survival rates. Cox proportional hazard models were used to identify the association between the risk of death and risk factors including gender, age, cancer stage, smoking history, alcohol-use history, calendar year of enrollment, and time-updated PM2.5, PM10, NO2 and O3 concentrations. The mortality rate was 68.2 per 100 persons per year of follow-up. In a multivariate analysis, gender, age, cancer stage, calendar year of enrollment, and time-varying residential concentration of PM2.5 were independently associated with the risk of death. The lower the annually averaged PM2.5 and PM10 concentrations, the higher the survival probability of the patient. As PM2.5 and PM10 were factors associated with a higher risk of death, lung cancer patients who are inhabitant in the area should reduce their exposure to high concentrations of PM2.5 and PM10 to increase survival rates.

Ambient Nanoparticles (PM0.1) Mapping in Thailand

“…Airborne PM is linked to increased mortality and morbidity in humans [15]. There is considerable evidence to show that PMs harm the respiratory, nervous, and cardiovascular systems [16][17][18]. Smaller particles (UFPs) have a large surface area and strong absorption/adsorption capability for various airborne contaminants.…”

Ambient air pollution as a time-varying covariate in the survival probability of childhood cancer patients in the upper Northern Thailand

“…This method can predict hazard ratios representing the risk or probability of the time-related occurrence of all-cause mortality for potential risk factors as baseline or timevarying variables. The potential risk factors in this study include gender, age at diagnosis, cancer stage, calendar year of registration (grouped as 2003-2013 or 2014-2018: the periods before and after the establishment of the national protocol for the treatment of childhood cancers), and the time-updated concentrations of PM 2.5 , PM 10 , NO 2 , SO 2 , CO, and O 3 during the study period [29]. For each continuous variable, we grouped the values by quartiles or separated them into two groups when appropriate or for the equivalent sample.…”

“…Currently, the available period for these datasets is from the beginning 2003 to the end of June 2022. They are suitable for conducting climatology computations, performing trend analysis, or comparative studies with other reanalysis models [29]. The reliability and validity reports on the CAMS Quality Assurance website for the data infer that the integrated system can be used to estimate the bias between observations and to separate high-quality data from inaccurate data.…”

“…Data for the cancer cases, including gender, age at diagnosis, and cancer characteristics (the type of cancer and cancer stage (SEER staging: localized, regional, or metastatic)) were obtained from the Chiang Mai Cancer Registry. The annual concentrations of air pollutants that the patients were exposed to from the year of diagnosis until the end of the study period were calculated from the air pollution data described in the previous subsection [29].…”

Ambient Nanoparticles (PM0.1) Mapping in Thailand

“…Airborne PM is linked to increased mortality and morbidity in humans [23]. There is considerable evidence to show that PMs harm the respiratory, nervous, and cardiovascular systems [24,25,26]. Smaller particles (UFPs) have a large surface area and strong absorption/adsorption capability for various airborne contaminants.…”