Abstract
We retrospectively analyzed non-small cell lung cancer (NSCLC) patients from a single center treated with pembrolizumab on the KEYNOTE-001 trial and evaluated the association between treatment-related adverse events (trAEs) and clinical outcomes. Investigators reported AEs on trial and graded them according to CTCAE v4.0, labeling them as unlikely, possibly, or probably treatment-related. AEs labeled as possibly/probably related were considered trAEs for this analysis. The relationship between the incidence of a trAE and clinical outcomes was evaluated. 97 NSCLC patients treated on KEYNOTE-001 at UCLA were evaluated. 10% (85/826) of AEs were trAEs, occurring in 40% (39/97) of patients. The most frequent trAEs were rash (20% pts), fatigue (6% pts), and hypothyroidism (6% pts). The 39 patients that experienced a trAE had increased ORR (38.5%), PFS (median 248 days), and OS (median 493 days), compared to the 58 patients that did not (ORR: 8.9%, PFS: median 60 days, OS: median 144.5 days). The observed association between trAEs and improved clinical outcome persisted when using Cox proportional hazards regression models to assess the confounding effect of covariates and mitigate guarantee-time bias. The association also remained when data was sub-stratified by grade, degree of association, and treatment-related select AE designation. This single center analysis revealed that trAEs predicted for improved clinical outcome with pembrolizumab, and when controlling for guarantee-time bias and plausible confounders, this association remained. This observed relationship adds to our understanding of anti–PD-1 therapy and could aid clinicians in identifying patients most likely to benefit from therapy.
Keywords: anti–PD-1, immunotherapy, non-small cell lung cancer, adverse events
Introduction
Immune-based cancer therapy has been in development for almost four decades (1–3), but the first immunotherapeutics approved for non-small cell lung cancer (NSCLC) were not until 2015, when the programmed cell death-1 (PD-1) inhibitors pembrolizumab and nivolumab were granted U.S. Food and Drug Administration approval (4–7). Because immunotherapy can have mechanisms of action different from conventional cytotoxic chemotherapy and targeted therapies, its side effects can vary as well (8–10). Treatment-related adverse events (trAEs) associated with anti–PD-1 therapy are thought to arise as a result of a robust, uninhibited immune response, resulting in primarily T cell–mediated autoimmunity and/or inflammation that is most commonly transient in nature but can be severe in some instances (8–11). Non-organ specific trAEs, such as fatigue, fevers, and chills, are commonly seen as a result of immune checkpoint inhibition (8–11). Organ-specific side effects can also occur in nearly any location throughout the body, but are commonly observed in the integumentary, gastrointestinal, endocrine, and hepatic systems (8–11). Of particular concern in patients with NSCLC is the occurrence of trAEs that affect the respiratory system, namely pneumonitis, and although these cases are rare, they can be fatal (6,9).
It has been hypothesized that certain patients can be primed to respond to immunotherapy due to heightened baseline “immunocompetence,” and evidence exists to suggest that patients who experience AEs related to immunotherapy are more likely to benefit from therapy (10,12–14). Importantly, the largest of evaluation to date (a pooled analysis of four clinical trials evaluating nivolumab in melanoma) found that treatment-related select AEs of any grade were associated with improved objective response rate (ORR) (15). However, others have not found a relationship between AEs associated with immunotherapy and clinical outcome (16). Because the association between AEs experienced by NSCLC patients on anti–PD-1 clinical trials and clinical outcome has not formally been evaluated, we pursued a retrospective analysis of clinical data obtained from the 97 NSCLC patients treated at our single center [The University of California, Los Angeles (UCLA)] as part of the KEYNOTE-001 trial and evaluated the association between trAEs and clinical outcomes.
Methods
Study Design
We performed a retrospective analysis of 97 NSCLC patients treated at UCLA with follow-up data available between August 2012 and December 2016 for KEYNOTE-001 (clinicaltrials.gov NCT01295827). A 98th patient was enrolled at UCLA but transferred care to another institution shortly after enrollment, so they were not included in the analysis because no follow-up data was available. Patients were treated with pembrolizumab intravenously at a dose of either 2 mg/kg every three weeks or 10 mg/kg every two or three weeks. Investigators reported AEs and graded them according to Common Terminology Criteria for Adverse Events v4.0 (CTCAE), labeling them as unlikely, possibly, or probably treatment-related. All AEs that were labeled as possibly or probably related to treatment were considered trAEs for our retrospective analysis, regardless of whether one type of trAE was reported multiple times within a particular patient. Investigators also had the ability to independently deem an AE as an immune related AE (irAE). We also retrospectively identified treatment-related select AEs, as defined by Weber et al., “AEs with a potential immunologic cause that need frequent monitoring and potential intervention with immune suppression and/or endocrine treatment” (15). A history of prior radiation therapy was defined as a patient having received any radiation for the treatment of NSCLC at any time point prior to the first cycle of pembrolizumab, as previously described (17). Finally, per protocol, patients had thyroid stimulating hormone (TSH), free thyroxine 4 (fT4), and triiodothyronine (T3) assessed at baseline (prior to initiation of therapy), cycle 2, and every other cycle thereafter (i.e. cycle 4, cycle 6, etc.). These parameters were also assessed at unscheduled visits between cycles and at safety follow-up. Tumor responses were evaluated using investigator-assessed, immune-related response criteria (irRC) initially at nine weeks (+/− one week), with subsequent computed tomography or magnetic resonance imaging every nine weeks (6).
Treatment Outcome Groups and Efficacy Analysis
Available efficacy data as of December 31, 2016, was included in all analyses. Three endpoints were included in the efficacy analysis: (i) Objective response rate (ORR), the proportion of patients who achieved a complete response or partial response, determined by irRC; (ii) Progression-free survival (PFS), the number of days between the first date of treatment with pembrolizumab to date of clinical progression as determined by the treating investigator, radiographic progression by investigator evaluated irRC, or death from any cause; and (iii) Overall survival (OS), the number of days between first date of treatment with pembrolizumab to date of death from any cause. All efficacy analyses were evaluated in the intent to treat (ITT) population that had follow-up data available (n=97).
Statistical Analysis
Clinical and demographic characteristics were compared using Fisher’s exact test for categorical variables, except as noted. PFS and OS curves were created with the Kaplan-Meier estimate and stratified by a history of a trAE. Kaplan-Meier estimates and comparisons between clinical/demographic characteristics were performed using GraphPad Prism v7 (Graphpad Software, Inc., San Diego, CA), wherein all tests were two-sided with p values <0.05 considered statistically significant.
Cox proportional hazards regression models were used to assess the effect of trAEs on survival outcomes (PFS and OS), adjusting for potential confounding factors. In the Cox proportional hazards regression models, the number of trAEs was modeled as a time-varying covariate. To assess the effect of trAEs on ORR, adjusting for potential confounders, a logistic regression model was used. In the logistic regression models, only the 65 patients on trial ≥9wks were included and only those trAEs that occurred ≤9wks after initiating therapy were considered. The number of trAEs was modeled as a time-varying covariate in the Cox proportional hazards regression models, and a landmark approach was employed in the logistic regression models because trAE status was unknown at trial initiation and because these approaches mitigate guarantee-time bias. ORRs were compared with odds ratios. R version 3.3.2 (www.R-project.org) was used for the Cox proportional hazards and logistic regression models with p values <0.05 considered statistically significant.
Results
Description of experienced AEs, trAEs, and treatment-related select AEs
826 AEs were reported on trial occurring in 97% (94/97) of the patients treated at UCLA who had follow-up data available. Of these 826 AEs, 10% (85/826) were deemed to be trAE (53 possibly treatment-related and 32 probably treatment-related), occurring in 40% (39/97) of the UCLA patients. 33 patients experienced a grade 1 trAE, 18 experienced a grade 2 trAE, and 3 experienced a grade ≥3 trAE. In contrast, 70.9% (351/495) of the 495 total NSCLC patients on trial experienced a trAE [8]. 11 irAEs were reported in the UCLA cohort, 9 of which were deemed to be treatment-related, and these occurred in 6 patients, 3 with pneumonitis and three with rash. Data regarding the frequency of treatment-related irAE occurrence in the 495 total NSCLC patients on trial has not been published to date. 55.3% (47/85) of the prospectively reported trAEs at UCLA were retrospectively identified as treatment-related select AEs, as previously defined (15) and occurred in 28.9% (28/97) of patients. Of the 97 patients treated at UCLA with follow-up data available, 95 were enrolled by one of two investigators. Investigator 1 enrolled 52 patients on trial, of which 39% (20/52) had a trAE, while investigator 2 enrolled 43 patients on trial, of which 42% (18/43) had a trAE.
The most frequent AEs experience by UCLA patients on trial were fatigue (50% of patients), pain (36%), and dyspnea (29%) (Supplementary Table S1), whereas the most frequent trAEs were rash (21%), fatigue (6%), and hypothyroidism (6%) (Table 1). When compared to the total study population, inclusive of the 97 patients treated at UCLA, the incidence of treatment-related hypothyroidism was nearly identical in the UCLA cohort. However, treatment-related rash was much more common in the UCLA cohort, which occurred in 21% of patients compared to only 9.7% in the total study population, whereas treatment-related fatigue was less common in the UCLA cohort, occurring in 6% of patients compared to 19.4% of patients in the total study population. Treatment-related pruritus was more common in the total study population, occurring in 10.7% of patients compared to 3% in the UCLA cohort. No treatment-related grade 5 events were noted in the UCLA cohort (Table 1).
Table 1.
trAEs that occurred in at least 2 of the 97 NSCLC patients treated on KEYNOTE-001 at UCLA. Of note, no grade 5 trAEs were experienced in this patient cohort.
| Treatment Related AEs Occurring in ≥ 2 Patients of UCLA Cohort (N=97) | |||
|---|---|---|---|
| AE Term | Grade 1 | Grade 2 | Grade 3 or 4 |
| rash | 18 (18.6) | 4 (4.1) | 0 |
| fatigue | 5 (5.2) | 3 (3.1) | 1 (1.0) |
| hypothyroidism | 1 (1.0) | 5 (5.2) | 0 |
| fever/chills | 4 (4.1) | 1 (1.0) | 0 |
| anorexia | 3 (3.1) | 1 (1.0) | 0 |
| pneumonitis | 1 (1.0) | 3 (3.1) | 2 (2.1) |
| pruritus | 2 (2.1) | 1 (1.0) | 0 |
| abdominal pain | 1 (1.0) | 1 (1.0) | 0 |
| worsening dyspnea | 0 (0.0) | 2 (2.1) | 0 |
| joint pain | 1 (1.0) | 1 (1.0) | 0 |
| edema | 2 (2.1) | 0 | 0 |
Abbreviation: AE, adverse event
Baseline clinical characteristics according to history of a trAE
Baseline clinical characteristics of the 97 patients evaluated were well-balanced between those that experienced a trAE and those that did not and were similar to the 495 total patients treated on trial at all sites, inclusive of the 97 UCLA patients (Table 2 and Supplementary Table S2). However, the presence of an EGFR mutation was much more common in the cohort of patients treated at UCLA compared to the total study population (31% and 15%, respectively), which coincided with a higher incidence of ‘never smokers’ in the UCLA cohort (44% compared to 25% in the total study population). The UCLA cohort was less heavily pretreated than the total study population (24% of patients with ≥3 previous lines of therapy in the UCLA cohort compared to 42% in the total study population). Patients that experienced a trAE were numerically more likely to be PD-L1+ (82% of patients) and less likely to be EGFR mutation positive (23% of patients) compared to those that did not experience a trAE (72% and 36%, respectively). The 39 patients that experienced a trAE had a much higher average number of AEs (12.5) compared to the 58 patients that did not experience a trAE (5.8), but the average number of a grade 3 or higher AEs was similar in both populations (1.2 and 1.3, respectively).
Table 2.
Demographics of 97 NSCLC UCLA patients treated on KEYNOTE-001 stratified by history of trAE at any time point. P-values were computed using Fisher’s exact test.
| Characteristic | trAE+ | trAE− | P value | ||
|---|---|---|---|---|---|
| (N=39) | (N=58) | ||||
| Age-year | |||||
| Median | 67 | 65 | |||
| Range | 32 – 78 | 36 – 83 | |||
| Gender - no. (%) | |||||
| Male | 22 | 56% | 28 | 48% | 0.4093 |
| Female | 17 | 44% | 30 | 52% | |
| Previous Therapy Lines - no. (%) | |||||
| 0 | 7 | 18% | 6 | 10% | 0.5967 |
| 1–3 | 23 | 59% | 38 | 66% | |
| ≥3 | 9 | 23% | 14 | 24% | |
| Smoking Status - no. (%) | |||||
| Ever | 24 | 62% | 30 | 52% | 0.4066 |
| Never | 15 | 38% | 28 | 48% | |
| PD-L1 Status - no. (%) | |||||
| Negative | 5 | 13% | 6 | 10% | 0.2116 |
| Positive | 32 | 82% | 42 | 72% | |
| Unknown | 2 | 5% | 10 | 17% | |
| PD-L1 Proportion Score - no. (%) | |||||
| Unknown | 11 | 28% | 10 | 17% | 0.5153 |
| ≤1 | 9 | 23% | 12 | 21% | |
| 1–49 | 14 | 36% | 24 | 41% | |
| ≥50 | 5 | 13% | 12 | 21% | |
| Histology - no. (%) | |||||
| Nonsquamous | 31 | 79% | 47 | 81% | 1 |
| Squamous Cell Carcinoma | 8 | 21% | 11 | 19% | |
| Targetable Mutations - no. (%) | |||||
| EGFR mutation | 9 | 23% | 21 | 36% | 0.1873 |
| ALK Translocation | 0 | 0% | 2 | 3% | 0.5185 |
| Number of AE Occurences per Patient - no. (%) | |||||
| <3 | 1 | 3% | 12 | 21% | <0.0001 |
| 3–7 | 12 | 31% | 32 | 55% | |
| >7 | 26 | 67% | 14 | 24% | |
| Average Number of AE's by Grade per Patient | |||||
| ≥Grade 3 | 1.2 | 1.3 | 0.8614 | ||
Effects of prior radiation therapy on the occurrence of a trAE
Because our patient cohort was less heavily pretreated than the total study population and we previously showed that patients in our cohort with a history of prior thoracic radiation therapy (TRT) had more overall treatment-related pulmonary toxicity (12·5% vs. 1·4%, p=0·046) compared to those without prior TRT (17), we assessed the influence of prior radiation therapy on the development of a trAE of any type. Prior TRT did not clearly influence the occurrence of a trAE, as 50% (12/24) of patients with a history of prior TRT had a trAE compared to 40% (27/73) of patients without prior history of TRT (p=0.338). We next evaluated the effect of any prior radiation therapy on the occurrence of a trAE and findings were similar – 47.6% (20/42) of patients with a history of prior radiation therapy experienced a trAE compared to 34.6% (19/55) of patients without a history of prior radiation therapy (p= 0.2154) (Supplementary Table S3).
Clinical outcomes stratified by history of trAEs
In the UCLA cohort of 97 patients with follow-up data available, an objective response rate (ORR) of 21%, median progression-free survival (PFS) of 64 days, and a median overall survival (OS) of 221 days was observed. The ORR in the total study population, 19.4%, was similar to that observed in the UCLA cohort, although both median PFS and median OS were longer in the total study population (111 and 365 days, respectively (6)). In the UCLA cohort, those that experienced a trAE had a higher ORR (38.5%), a longer median PFS (248 days), and longer median OS (493 days) compared to patients that did not experience a trAE (ORR: 8.9%; PFS: median 60 days; and OS: median 144.5 days) (Supplementary Fig. S1A). These relationships persisted when further stratifying patients based on degree of trAE attribution (possible/probable) and when the analysis was limited to only include grade 2 or higher trAEs (Supplementary Table S4). When restricting this analysis to include only the 47 treatment-related select AEs experienced by patients on trial, those that experienced a treatment-related select AE had a higher ORR (39.3%), a longer median PFS (248 days), and longer median OS (493 days) compared to patients who did not (ORR: 13%; PFS: median 61 days; and OS: median 158 days) (Supplementary Fig. S1B).
Further evaluation of the association between a trAE and clinical outcomes
To summarily assess the confounding effect of covariates on the observed association between trAEs and improved clinical outcomes, as well as mitigate guarantee-time bias, statistical models incorporating clinicopathologic covariates were generated. In the Cox proportional hazards regression models, the number of trAEs was incorporated as a time-varying covariate to control for guarantee-time bias. For PFS, the unadjusted Cox proportional hazards regression model revealed a trend towards improved PFS in patients with increasing numbers of trAEs [HR (95% CI): 0.81 (0.65, 1.01); p= 0.067]. This relationship became stronger in the adjusted model that took into account known predictors of response to anti-PD-1 therapy in NSCLC [HR (95% CI): 0.75 (0.56, 0.99); p= 0.043]. For OS, both the unadjusted and adjusted Cox proportional hazards regression models support a strong association between improved OS in patients with increasing numbers of trAEs [Unadjusted Model HR (95% CI): 0.77 (0.63, 0.94); p= 0.011 and Adjusted Model HR (95% CI): 0.75 (0.58, 0.96); p= 0.021]. Utilizing logistic regression models to assess the association between ORR and the number of trAEs experienced by patients, the adjusted model incorporating PD-L1 proportion score and EGFR mutational status, suggested a trend towards improved ORR in patients that experienced trAEs [Unadjusted Model HR (95% CI): 1.27 (0.81, 1.99); p= 0.306 and Adjusted Model HR (95% CI): 2.02 (0.87, 4.69); p= 0.101]. To control for guarantee-time bias in the logistic regression model assessing ORR, a landmark approach was employed wherein only the 65 patients on trial ≥9wks were included and only those trAEs that occurred ≤9wks after initiating therapy were considered (Table 3).
Table 3.
| a: Cox proportional hazards models were created for progression-free survival (PFS) with number of treatment related adverse events (trAEs) included as a time-varying covariate. Listed are results from both unadjusted model and adjusted models. Hazard ratio estimates marked ‘(+1)’ correspond to the incremental effect of a unit increase in the relevant predictor. | ||
|---|---|---|
| Progression-Free Survival (Unadjusted Model) | ||
| Effect | HR (95% CI) | P |
| Number of trAEs (+1) | 0.81 (0.65, 1.01) | 0.067 |
| Progression-Free Survival (Adjusted Model) | ||
|---|---|---|
| Effect | HR (95% CI) | P |
| Number of trAEs (+1) | 0.75 (0.56, 0.99) | 0.043 |
| Female | 0.80 (0.48, 1.35) | 0.409 |
| Age at Trial Start (+1y) | 0.97 (0.95, 1.00) | 0.036 |
| Number of Previous Lines of Therapy (+1) | 1.03 (0.86, 1.24) | 0.760 |
| PD-L1 Proportion Score (Ref: ≤1) | ||
| 1–49 | 1.13 (0.63, 2.02) | 0.686 |
| ≥50 | 1.03 (0.46, 2.28) | 0.948 |
| EGFR Mutations | 1.51 (0.80, 2.84) | 0.204 |
| Ever Smoker | 0.93 (0.48, 1.80) | 0.820 |
| Squamous | 1.01 (0.52, 1.95) | 0.972 |
| b: Cox proportional hazards models were created for overall survival (OS) with number of treatment related adverse events (trAEs) included as a time-varying covariate. Listed are results from both unadjusted model and adjusted models. Hazard ratio estimates marked ‘(+1)’ correspond to the incremental effect of a unit increase in the relevant predictor. | ||
|---|---|---|
| Overall Survival (Unadjusted Model) | ||
| Effect | HR (95% CI) | P |
| Number of trAEs (+1) | 0.77 (0.63, 0.94) | 0.011 |
| Overall Survival (Adjusted Model) | ||
|---|---|---|
| Effect | HR (95% CI) | P |
| Number of trAEs (+1) | 0.75 (0.58, 0.96) | 0.021 |
| Female | 0.92 (0.56, 1.51) | 0.738 |
| Age at Trial Start (+1y) | 0.99 (0.96, 1.01) | 0.285 |
| Number of Previous Lines of Therapy (+1) | 1.08 (0.91, 1.28) | 0.363 |
| PD-L1 Proportion Score (Ref: ≤1) | ||
| 1–49 | 1.18 (0.67, 2.06) | 0.566 |
| ≥50 | 1.38 (0.63, 3.02) | 0.420 |
| EGFR Mutations | 0.74 (0.40, 1.38) | 0.345 |
| Ever Smoker | 0.72 (0.39, 1.34) | 0.302 |
| Squamous | 0.98 (0.49, 1.96) | 0.950 |
| c: Logistic regression models were created for objective response with number of treatment related adverse events (trAEs) included as a covariate. To control for guarantee bias, only the 65 patients on trial ≥9wks were included and only those trAEs that occurred ≤9wks after initiating therapy were considered. Listed are results from both unadjusted model and adjusted models. ORRs are compared with odds ratios and odds ratio estimates marked ‘(+1)’ correspond to the incremental effect of a unit increase in the relevant predictor. | ||
|---|---|---|
| Objective Response Rate (Unadjusted Model) | ||
| Effect | OR (95% CI) | P |
| Number of trAEs (+1) | 1.27 (0.81, 1.99) | 0.306 |
| Objective Response Rate (Adjusted Model) | ||
|---|---|---|
| Effect | OR (95% CI) | P |
| Number of trAEs (+1) | 2.02 (0.87, 4.69) | 0.101 |
| PD-L1 Proportion Score (Ref: ≤1) | ||
| 1–49 | 3.94 (0.67, 23.10) | 0.129 |
| ≥50 | 26.64 (2.85, 249.00) | 0.004 |
| EGFR Mutations | 1.07 (0.18, 6.47) | 0.937 |
Treatment-related AE subgroup analyses
The same Cox proportional hazards and logistic regression models discussed above were utilized to assess the association between clinical outcomes and the presence or absence of the following four independent trAE subcategories: treatment-related select AEs (n=47), possible trAE (n=53), probable trAE (n=32), and a grade 2 or higher trAE (n=31). The unadjusted Cox proportional hazards regression model revealed a trend towards improved PFS in patients with increasing numbers of treatment-related select AEs, whereas the adjusted model revealed a clear association [Unadjusted Model HR (95% CI): 0.76 (0.55, 1.05); p= 0.097 and Adjusted Model HR (95% CI): 0.62 (0.40, 0.96); p= 0.034]. For OS, both the unadjusted and adjusted Cox proportional hazards regression models showed a trend towards improved OS in patients with increasing numbers of treatment-related select AEs [Unadjusted Model HR (95% CI): 0.77 (0.58, 1.03); p= 0.079 and Adjusted Model HR (95% CI): 0.72 (0.49, 1.05); p= 0.088]. Neither the unadjusted or adjusted logistic regression models evidenced a clear association between a treatment-related select AE and improved ORR [Unadjusted Model OR (95% CI): 1.15 (0.53, 2.50); p= 0.729 and Adjusted Model OR (95% CI): 1.67 (0.55, 5.09); p= 0.364] (Supplementary Table S5).
To assess the association between a more severe trAE, defined as grade 2 or higher, and clinical outcomes, we incorporated only the 31 trAEs that were grade 2 or higher into the Cox proportional hazards and logistic regression models. In the adjusted models, but not the unadjusted models, a trend towards improved PFS, OS, and ORR was seen in the patients that experienced a grade 2 or higher trAE compared to those that did not (All p-values in the adjusted models <0.10, whereas all p values in unadjusted models >0.10). Probable trAEs were clearly associated with improved PFS and OS, in both unadjusted and adjusted models (All p values <0.015), whereas the association between a possible trAE and PFS/OS was less clear (All p values in both unadjusted and adjusted models >0.10). A strong association between a possible or probable trAE and improved ORR was not observed in the logistic regression models.
Association between abnormal thyroid indices and clinical outcomes
Because treatment-related hypothyroidism was the most predictive trAE in our cohort, ORR 83.3% (5/6), we investigated how changes in thyroid indices [TSH, fT4, and T3] related to pembrolizumab activity. 97.9% (95/97) of patients treated at UCLA with available clinical follow-up data had at least a baseline set of thyroid indices available for analysis. 74.7% (68/97) of patients had ≥3 sets of values. The association between abnormal thyroid indices in the former group of 95 patients and clinical outcomes was evaluated.
32.6% (31/95) of these 95 patients had at least one abnormal TSH noted on trial. Of these 31 patients, 24 had an elevated TSH, whereas 14 had a decreased TSH recorded. Seven of these patients had both an elevated and decreased TSH at independent time points. Patients with an abnormal TSH had a higher ORR, 35.5% (11/31), than those without, 14.1% (9/64) (p=0.0296). Patients with an elevated TSH had an ORR of 41.7% (10/24), whereas those with a decreased TSH had an ORR of 57.1% (8/14) compared to an ORR of 14.1% (10/71) and 14.8% (12/81) for patients without an elevated or decreased TSH, respectively (Elevated TSH: p=0.0079; Decreased TSH: p=0.0014). All 7 patients with evidence of variable thyroid function on trial, defined as both an elevated and decreased TSH noted at independent time points, had an objective response on trial (Supplementary Table S6A).
We then incorporated the timing of TSH abnormality identification into our analysis because the biological implications of a baseline abnormality, prior to therapy, are different than those of an abnormality that arose on trial. In this analysis, only patients without a baseline TSH abnormality were considered to have an “acquired” TSH abnormality. The ORR for patients with an acquired TSH abnormality was numerically greater than for patients with a baseline abnormality, with an ORR of 42.9% (9/21) in the former group, compared to 20% (2/10) in the latter group (p=0.2617) (Supplementary Table S6D).
An abnormal fT4 or T3 on trial were also both independently associated with improved ORR. Specifically, an abnormal fT4 was noted in 10 patients, with an ORR of 50% in this group compared to 17.7% (10/85) in patients without an abnormal fT4 (p=0.0317). Nineteen patients had an abnormal T3, with an ORR of 47.4% (9/19) in this group compared to 14.5% (11/76) in those patients without an abnormal T3 (p=0.0037). Neither of the 2 patients with an abnormal baseline fT4 had an objective response, whereas the ORR for patients with an acquired fT4 abnormality was 62.5% (5/8). Six patients had an abnormal T3 at baseline, with an ORR of 33.3% (2/6) in this group, whereas the ORR for patients with an acquired T3 abnormality was 53.9% (7/13). Eight of 16 patients with a low T3 had an objective response (ORR: 50%), whereas only 1 of 3 patients with a high T3 had an objective response (ORR: 33.3%). Similar patterns were observed for fT4 – 80% (4/5) patients with a low fT4 had an objective response compared to only 28.6% (2/7) of patients with an elevated fT4 (Supplementary Tables S6B–D).
Discussion
This single center, retrospective analysis revealed that a trAE predicted for improved clinical outcome with pembrolizumab. To capture all possible AEs associated with pembrolizumab therapy on trial, rather than restricting our analysis to the very low number of AEs deemed by the investigator to be an irAEs, we chose to evaluate all AEs considered at least possibly related to the study drug. In fact, only 6 patients in the UCLA cohort were reported to have an irAE at least possibly related to pembrolizumab, 3 with pneumonitis and 3 with rash. However, 6 patients experienced treatment-related hypothyroidism, a well-documented AE associated with immune checkpoint inhibitors, illustrating that real-time attribution of toxicity with a new drug class can be difficult (9,11). To limit bias introduced by this more inclusive approach to trAE inclusion, we performed a retrospective analysis to identify treatment-related select AEs and found a strong association between the occurrence of a treatment-related select AE and improved clinical outcomes. Taken together, the findings from both our trAE analysis and retrospectively filtered treatment-related select AE analysis support the hypothesis that those patients responding to therapy may also disproportionately experience treatment-related side effects (11,15,18).
Consistent with the experience with other immune checkpoint inhibitors in NSCLC (19), almost every NSCLC patient treated on KEYNOTE-001 at UCLA experienced an AE. However, only 10% of the AEs reported were deemed by the investigator to be treatment-related. These 85 trAE events occurred in 40% of patients on trial, which was lower than the overall numbers reported for the 495 total patients enrolled on KEYNOTE-001, inclusive of the UCLA cohort, where 70.9% of patients experienced a trAE (6). This difference may have been a result of our investigators’ increased level of comfort with anti–PD-1 therapy. Specifically, although nearly 100 patients were treated at our site, many sites would have more limited experience with anti–PD-1 therapy during the time that these agents were not widely available. The significantly higher level of experience with anti–PD-1 therapy at UCLA may have led to a more discerning classification of treatment association in comparison to investigators at other sites with less experience with these therapies. Because we do not have access to adverse event data for the total study population stratified by individual investigators, we cannot further evaluate this hypothesis. However, we were able assure that the lower rate of reporting at UCLA was not simply a result of a specific investigator’s assessments because internal consistency was present within the UCLA cohort with respect to the rate at which AEs were deemed treatment-related.
Differences in demographics between the UCLA cohort and the total study population may be another possible explanation for the observed difference in the percentage of patients that experienced a trAE in the UCLA cohort compared to the total study population. Specifically, there was a much higher incidence of ‘never smoking’, less heavily pretreated, EGFR mutation-positive patients that were less likely to experience a trAE on trial in the UCLA cohort. Again, data is not available regarding the rate at which these subpopulations experienced a trAE in the total study population, so the influence of their overrepresentation in our cohort cannot be definitively identified. However, to attempt to address the possible effects of a less heavily pretreated population in the UCLA cohort we evaluated the influence of prior radiation therapy on the subsequent development of a trAE of any type in our patient cohort and found no clear association. This is despite the fact, that patients in our cohort with a history of prior thoracic radiation therapy (TRT) had more overall treatment-related pulmonary toxicity compared to those without prior TRT, as previously reported (17). Finally, guarantee-time bias, the fact that patients on trial longer would be more likely to develop a trAE, may also have contributed to the lower number of patients experiencing a trAE in the UCLA cohort compared to the total study population, as the median PFS in the total study population was almost twice as long as the UCLA cohort (111 vs 64 days).
The occurrence of a trAE was not associated with the myriad of clinicopathological characteristics available for evaluation, emphasizing the robust nature of this observed association – one that cannot be otherwise explained by known predictors of response to PD-1 blockade. To further evaluate the independent nature of the observed association between a trAE and improved clinical outcomes, statistical models incorporating these clinicopathologic covariates were generated. The results from these models further strengthened the notion that this association was not due to confounding variables. All trAEs experienced on trial by ≥2 patients have been described with anti–PD-1 blockade (8,9,11,20). That said, certain trAEs appeared to be more predictive of response to anti–PD-1 therapy in our patient cohort, such as hypothyroidism, where the occurrence of treatment-related hypothyroidism was associated with objective response to therapy in all but one of the patients who experienced this trAE.
Because the CTCAE v4 criteria for grading hypothyroidism does not take into account actual thyroid indices and is based upon symptoms and need for replacement therapy, we evaluated the association between an abnormal TSH, fT4, or T3 observed on trial and clinical outcomes. Abnormalities in TSH, fT4, or T3 strongly associated with improved clinical outcomes on trial, with acquired abnormalities (first occurrence after administration of pembrolizumab) more predictive than baseline abnormalities and abnormally low values more predictive than abnormally high values. The strong correlation observed between treatment-related hypothyroidism, as well as abnormal thyroid indices, and response to pembrolizumab is consistent with the findings of others (15,21) and certainly warrants further evaluation.
In the 97 patients treated at UCLA on KEYNOTE-001 that had follow-up available, the patients that experienced a trAE or a treatment-related select AE had improved outcomes. These findings are consistent with experience with checkpoint inhibition in melanoma, where a correlation between improved clinical outcomes and AEs related to therapy has been observed (10,13–15). For example, those metastatic melanoma patients treated with anti–CTLA-4 therapy in combination with a peptide vaccine, who experienced grade 3/4 autoimmune toxicity, had a much higher clinical response rate, 36%, compared to those with no autoimmune toxicity, 5% (12). However, data on this subject is conflicting, as others have found no association between immune checkpoint-related AEs and response to checkpoint blockade in melanoma (16). This observed association between response to pembrolizumab and treatment-related side effects has clinical relevance, as the systemic side effects experienced as a result of pembrolizumab could serve as a proxy for response to therapy, similar to rash in EGFR tyrosine kinase inhibitor therapy (22–24).
In terms of generalizability of our findings to the use of PD-1/PD-L1 blockade in NSCLC, it must be understood that by its very nature, any analysis assessing an association between AEs, as reported prospectively by investigators, and clinical data is entirely reliant on an individual investigator’s practice of AE reporting. Although the standardized CTCAE criteria establish a validated framework by which AEs can and should be reported, every investigator still has complete autonomy with respect to event reporting. In our analysis, we have attempted to mitigate this limitation in a number of ways. First, our central analysis was based on an agnostic approach to trAE inclusion. This approach was chosen to mitigate AE selection bias introduced by retrospective filtering of AEs for those considered most likely to be a result of therapy. As PD-1/PD-L1 blockade is a relatively new therapeutic approach in NSCLC, it seems premature to assert that we know precisely which AEs are a result of therapy and which are not. Second, subanalyses were performed to address potential sources of bias within each investigator’s AE reporting pattern. However, these subanalyses are exploratory in nature, and due to multiplicity issues, the results should be interpreted with caution. That said, the association between improved clinical outcomes and a trAE remained robust when stratifying the inclusion of an AE by the degree of attribution (possible, probable) to pembrolizumab and also when restricting the analysis to more severe trAEs, defined as grade 2 or higher. ≥95% of patients experienced an AE of any relation to pembrolizumab or an AE considered unlikely related to pembrolizumab, so stratifying patients by the presence or absence of such an AE and correlating to outcomes does not yield meaningful information. Although the benefits of an agnostic approach to trAE inclusion are clear, we did perform retrospective filtering of AEs reported on trial to include only the 47 events considered treatment-related select AEs (15). In so doing, we attempted to mitigate the bias of including too broad a group of trAEs in our analysis, inclusive of AEs that may not be related to pembrolizumab mechanistically, and the results of this analysis largely corroborated the central findings of our agnostic approach. Cox proportional hazards and logistic regression models were generated to minimize guarantee-time bias, wherein the number of trAEs was modeled as a time-varying covariate in the Cox proportional hazards regression model and a landmark approach was employed in the logistic regression models because trAE status was unknown at trial initiation. The results of these models clearly support the observed association between the occurrence of a trAE and improved clinical outcomes in our patient cohort and suggest this association is largely independent of guarantee-time bias. However, the seven factors included in the multivariable models were nearly all non-significant in their predictive nature for benefit with pembrolizumab in our patient cohort, likely due to the limited number of patients available for analysis and associated study events. Finally, because some CTCAE v4 criteria are based upon symptomatology or medical interventions required rather than more objective endpoints, we performed a subanalysis of laboratory values for the most predictive trAE in our cohort, thyroid dysfunction, and found compelling preliminary data that the development of thyroid dysfunction on trial was highly predictive of treatment efficacy. Ultimately, it will take many more similar analyses in NSCLC to accurately characterize the type of adverse events mechanistically associated with PD-1 blockade and ascertain the generalizability of our findings, but we strongly believe that the analysis presented herein provides a reasonable starting place.
Although our retrospective analysis has the weakness of being conducted at a single center representing only approximately 20% of patients on trial, the strength is that a limited number of investigators assessed if an event was an AE and was treatment-related. Given the clear internal consistency of our data set, we employed an agnostic approach with respect to treatment-related AE inclusion, to assure all side effects of therapy were considered. The central conclusion of our analysis, namely that AEs believed to be associated with PD-1 blockade are associated with improved patient outcomes, is further supported by the retrospective treatment-related select AE analysis included. Future work will focus on evaluating the association between trAEs and response to anti–PD-1 therapy in a larger patient population and with other NSCLC immunotherapeutics.
Supplementary Material
Acknowledgments
Dr. Lisberg reports honoraria from AstraZeneca.
Dr. Garon reports funds to his institution from AstraZenca, Boehringer Ingelheim, Bristol Myers Squibb, Eli Lilly, Genentech, Mirati, Merck, Pfizer, and Novartis.
Dr. Goldman reports research grants from AstraZeneca, Bristol Myers Squibb, Roche/Genentech, and Merck; and honoraria for speaking for Merck.
Funding/Support: Dr. Garon was in part supported by the One Ball Matt Memorial Golf Tournament andR01 CA208403
Footnotes
Conflict of Interest Statement
The remaining authors have no conflicts of interest to report.
Author Contributions:
Study Concept and Design: Lisberg A, Tucker DA, Garon EB, Wolf B, Goldman JW.
Acquisition, analysis, and interpretation of the data: Lisberg A, Tucker DA, Garon EB, Wolf B, Goldman JW, Carroll J, Hardy A, Morris K, Linares P, Adame C, Spiegel M, Wells C, McKenzie J, Abarca P, Bornazyan K, Hunt J, Moghadam N, Chong N, Nameth D, Marx C, Madrigal J, Ledezma B, Mendenhall M, N Shaverdian
Drafting of Manuscript: Lisberg A, Tucker DA, Garon EB, Wolf B, Goldman JW
Critical Revision of Manuscript for Important Intellectual Content: Lisberg A, Tucker DA, Garon EB, Wolf B, Goldman JW, Carroll J, Hardy A, Morris K, Linares P, Adame C, Spiegel M, Wells C, McKenzie J, Abarca P, Bornazyan K, Hunt J, Moghadam N, Chong N, Nameth D, Marx C, Madrigal J, Ledezma B, Mendenhall M
Statistical Analysis: Lisberg A, Tucker DA, Garon EB, Wolf B, D Elashoff, S Vangala
Obtained Funding: Garon EB
Administrative, technical, or material support: Carroll J, Hardy A, Morris K, Linares P, Adame C, Spiegel M, Wells C, McKenzie J, Abarca P, Bornazyan K, Hunt J, Moghadam N, Chong N, Nameth D, Marx C, Madrigal J, Ledezma B, Mendenhall M
Study supervision: Garon EB, Goldman JW
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