Abstract

Multiple immune checkpoint inhibitors have been on the market for metastatic non-small-cell lung cancer(NSCLC) and advanced small cell lung cancer(SCLC) since 2014. This class of therapies are expensive and can be healthcare resource use (HRU) intensive. We aimed to analyze the HRU among pembrolizumab, nivolumab, and atezolizumab in patients with metastatic lung cancer using real-world data. Adult patients with metastatic lung cancer(‘162.9’, ‘C34.90’) taking pembrolizumab, nivolumab or atezolizumab were identified from IBM MarketScan Commercial database from 2014 to 2018. Baseline characteristics were compared and reported using appropriate statistics. Crude hospital admissions, length of stay, clinic visits, out-of-pocket cost, total net payments were analyzed and reported per patient per year. A total of 1,101 patients were identified: pembrolizumab=181, nivolumab=889, atezolizumab=31. Mean ages are 55.9yo, 57.4yo and 54.3yo for patients with pembrolizumab-, nivolumab- and atezolizumab-based therapy respectively. Females represent about half of the population in all groups(pembrolizumab=52.5%, nivolumab=50.4%, atezolizumab=51.6%). Hospital admissions are similar among all groups (1.1, 1.1 and 0.9 respectively). Length of stay is shortest for nivolumab group (9.8 days, CI[9.03,10.61] ) and longest in atezolizumab group(12.2 days, CI[0.47-23.91]). Patients in nivolumab group have the most clinic visits (31.7 visits, CI[30.23-33.20]) and the ones in pembrolizumab group have the least(27.1 visits,CI[24.48-29.65]) per patient per year. Out-of-pocket cost is the least in atezolizumab group ($1028.79,CI[581.73-1475.86]) (pembrolizumab=$1129.29 CI[948.05-1310.52], nivolumab=$1311.54 CI[1142.86-1480.21]) whereas total net payment($151,821.36 CI[112,316.54- 191326.18])(pembrolizumab=$148,109.40 CI[128,874.92-167,343.88], nivolumab=$128,014.78 CI[120,346.62- 135,682.95]) is the most in this group. The HRU are highly likely to be different among pembrolizumab, nivolumab and atezolizumab in metastatic lung cancer population, especially in length of hospital stay, clinic visits and medical costs. However, since these groups are unbalanced in our study for standard comparison statistics, results can be bias. We would like to use entropy-balancing re-weight the unbalanced groups for further analysis in the future.

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