Impact of pseudoprogression and treatment beyond progression on outcome in patients with non-small cell lung cancer treated with immune checkpoint inhibitors

Abstract

Background: Immune checkpoint inhibitors (ICI) have become an important treatment option for nonsmall cell lung cancer (NSCLC). We aimed to evaluate the clinical impact of pseudoprogression (PsP) and treatment beyond RECIST1.1-defined progressive disease (TBP) on outcome in NSCLC patients treated with ICI. Methods: NSCLC patients treated with ICI between Mar 2016 and July 2018 were recruited in a consecutive manner. Response was assessed every 8-12 weeks using RECIST1.1 and iRECIST. Based on iRECIST, PsP was defined as progressive disease (PD) on RECIST1.1 subsequently reset to non-PD categories. Using log-rank test, progression-free survival (PFS) was compared between patients with and without PsP, and overall survival (OS) was compared between patients treated with and without TBP. The impact of TBP on OS was evaluated through multivariate Cox proportional hazard models. Results: Of the 189 patients, seven (3.7%) experienced PsP which mostly occurred approximately 3 months after baseline. The median PFS was significantly longer in patients with PsP (not reached) than those without PsP (3.8 months, P = .02). Among patients who demonstrated PD according to RECIST1.1, median OS was significantly longer in patients with TBP (17.2 months) than those without TBP (7.4 months, P < .001). On multivariate analysis adjusting other covariates, TBP (HR, 0.4; 95% CI, 0.2-0.7) remained as a significant protective factor for mortality. Conclusion: PsP occurred in 3.7% of NSCLC patients under ICI treatment. Based on iRECIST scheme, PsP and TBP may be associated with survival benefit.

Definition, Incidence, and Challenges for Assessment of Hyperprogressive Disease During Cancer Treatment With Immune Checkpoint Inhibitors

“… 1 However, atypical patterns of response, such as pseudoprogression and hyperprogressive disease (HPD), have been observed in cancers treated with ICIs. 2 , 3 …”

Comparison of RECIST 1.1 and iRECIST in Patients Treated with Immune Checkpoint Inhibitors: A Systematic Review and Meta-Analysis

“…The study search process is shown in Figure 1 . The characteristics of the 11 studies [ 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 ] including 6210 patients are summarized in Table 1 . One study was a pooled analysis of individual patient data (IPD) from 14 Food and Drug Administration (FDA)-approved randomized controlld trials (RCTs), one was an RCT, one was a phase II clinical trial, and eight were observational studies (1 prospective study and 7 retrospective studies).…”

“…Although iRECIST captured the benefit of ICI treatment in a subset of patients which RECIST 1.1 did not, and significantly prolonged PFS compared to RECIST 1.1, the magnitude of benefit was modest (3.9% of patients with pseudoprogression and PFS prolongation by 0.46 months), and these results should be interpreted with caution concerning the benefit and drawbacks of iRECIST application in clinical trial and practice [ 20 , 23 ]. While the application of iRECIST is beneficial to fully investigate the atypical response such as pseudoprogression and treatment efficacy, it adds considerable burden in imaging interpretation, data management, statistical analysis, cost, and potential risk of maintaining futile treatment.…”

“…However, controversy remains as the incidence of pseudoprogression is low, less than 10% [ 23 ] Treatment beyond progression might have risks of continuing futile treatment and delaying switch to other treatment options in patients with true progression. Although recent studies demonstrated that treatment beyond progression can provide the benefit of overall survival [ 20 ], further studies are necessary to evaluate the survival benefit of treatment beyond progression based on iRECIST.…”

“…The following data were extracted: (a) study characteristics including authors, year of publication, and study design; (b) demographic and clinical characteristics of the patients including sample size, type of cancer, and type of ICIs; (c) response-related endpoints based on RECIST 1.1 and iRECIST: ORR and iORR, and DCR and iDCR; and (d) data required to estimate PFS and iPFS as survival endpoints based on RECIST 1.1 and iRECIST, respectively [ 30 , 31 ]. In five studies [ 14 , 15 , 18 , 20 , 21 ], according to methods proposed by Guyot et al, individual patient data were reconstructed by extracting data from the Kaplan–Meier curves using digital software (WebPlotDizitizer) to estimate the time-dependent probability of PFS [ 27 ]. Definitions of each endpoint are detailed below.…”