Real-World EQ5D Health Utility Scores for Patients With Metastatic Lung Cancer by Molecular Alteration and Response to Therapy

Accepted Manuscript Real-World EQ5D Health Utility Scores for Metastatic Lung Cancer Patients by Molecular Alteration and Response to Therapy Catherine Labbé, Yvonne Leung, João Gabriel Silva Lemes, Erin Stewart, Catherine Brown, Andrea Perez Cosio, Mark Doherty, Grainne M. O’Kane, Devalben Patel, Nicholas Cheng, Mindy Liang, Gursharan Gill, Alexandra Rett, Hiten Naik, Lawson Eng, Nicole Mittmann, Natasha B. Leighl, Penelope A. Bradbury, Frances A. Shepherd, Wei Xu, Geoffrey Liu, Doris Howell PII:

S1525-7304(16)30391-6

DOI:

10.1016/j.cllc.2016.12.015

Reference:

CLLC 591

To appear in:

Clinical Lung Cancer

Received Date: 14 July 2016 Revised Date:

20 December 2016

Accepted Date: 20 December 2016

Please cite this article as: Labbé C, Leung Y, Silva Lemes JG, Stewart E, Brown C, Cosio AP, Doherty M, O’Kane GM, Patel D, Cheng N, Liang M, Gill G, Rett A, Naik H, Eng L, Mittmann N, Leighl NB, Bradbury PA, Shepherd FA, Xu W, Liu G, Howell D, Real-World EQ5D Health Utility Scores for Metastatic Lung Cancer Patients by Molecular Alteration and Response to Therapy, Clinical Lung Cancer (2017), doi: 10.1016/j.cllc.2016.12.015. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

ACCEPTED MANUSCRIPT Real-World EQ5D Health Utility Scores for Metastatic Lung Cancer Patients by Molecular Alteration and Response to Therapy

610 University Ave, Toronto, Ontario, M5G2M9, Canada Tel: 416-946-4501 ext 3428, Fax: 416-946-6546 E-mail: [email protected]

M AN U

Authors

SC

Corresponding author: Geoffrey Liu

RI PT

Word count: abstract: 247 words; text: 3410 words; 24 references; 3 tables; 1 figure, 5 supplementary tables, 2 supplementary figures.

Catherine Labbé1, Yvonne Leung2, João Gabriel Silva Lemes3, Erin Stewart2, Catherine Brown2, Andrea Perez Cosio2, Mark Doherty2, Grainne M. O’Kane2, Devalben Patel2, Nicholas Cheng2, Mindy Liang2, Gursharan Gill2, Alexandra Rett2, Hiten Naik2, Lawson Eng2, Nicole Mittmann4, Natasha B. Leighl2, Penelope A. Bradbury2, Frances A. Shepherd2, Wei Xu2, Geoffrey Liu2*, Doris Howell2* 1

2

TE D

Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada; Institut Universitaire de Cardiologie et de Pneumologie de Québec, Québec, QC, Canada. Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada.

3

4

EP

Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada (Scholar of the CNPq-Brazil).

AC C

Health Outcomes and PharmacoEconomics (HOPE) Research Centre, Sunnybrook Research Institute, Toronto, ON Canada. *DH and GL contributed equally Disclosures – Alan B. Brown Chair in Molecular Genomics and Lusi Wong Family Fund provided support. Dr. Liu has received honoraria from AstraZeneca, Roche, Pfizer, Novartis, Takeda, and Merck. Natasha B. Leighl has institutional funding from Novartis, and has received honoraria from AstraZeneca. Frances A. Shepherd has received honoraria for advisory boards for AstraZeneca, Boehringer Ingelheim, Bristol-Myers Squibb, Eli Lilly, Merck Canada, Pfizer and Roche-Genentech, has received payment for consulting for Eli Lilly, and holds investments in Eli Lilly and AstraZeneca. For the remaining authors none was declared. Keywords: health utility scores, EQ5D, EGFR, ALK, metastatic lung cancer. 1

ACCEPTED MANUSCRIPT MICROABSTRACT

There is limited data outside of clinical trials on health utility scores (HUS) in metastatic lung

RI PT

cancer patients. This longitudinal cohort study evaluated EQ5D-3L-derived HUS in 475 outpatients. Mean scores were higher in patients carrying driver mutations stable on targeted treatments, than in patients without alterations stable on chemotherapy. Such differences

M AN U

CLINICAL PRACTICE POINTS

SC

should be considered in economic analyses of upcoming treatments.

Health utility scores (HUS) in lung cancer patients have been inconsistently reported in clinical trials evaluating new therapies. Treatment response has been demonstrated to result

TE D

in utility gain, as well as being on ALK tyrosine kinase inhibitors (TKIs), as opposed to chemotherapy. Our study is the first to report real-word HUS in metastatic lung cancer patients, specifically within subgroups carrying different molecular alterations and under

EP

various treatment-dependent disease states. Indeed, mean HUS were higher in patients carrying driver mutations stable on targeted treatments, than in patients without alterations

AC C

stable on chemotherapy. We also demonstrated an inverse relationship between treatmentrelated toxicities and HUS. Our findings emphasize that pharmacoeconomic analyses of upcoming therapies should incorporate specific HUS for molecular alterations and response to therapy.

2

ACCEPTED MANUSCRIPT ABSTRACT Introduction: Economic analyses of upcoming treatments for lung cancer benefit from realworld health utility scores (HUS) in an era of targeted therapy.

RI PT

Methods: A longitudinal cohort study at Princess Margaret Cancer Centre evaluated 1571 EQ5D-3L-derived HUS in 475 outpatients with metastatic lung cancer across various disease states. Patients with EGFR (n=183) and ALK (n=38) driver alterations were enriched through

SC

targeted enrolment; patients with wildtype non-small cell lung cancer (WT NSCLC; n=224) and small cell lung cancer (SCLC; n=30) were sampled randomly.

M AN U

Results: For patients stable on most appropriate treatment, mean HUS were 0.81 and 0.82 in patients receiving EGFR and ALK tyrosine kinase inhibitors (TKIs) respectively (with similar HUS across agents), which were higher than WT NSCLC (0.78, p=0.04) and SCLC patients receiving chemotherapy (0.72, p=0.06). In mutation-specific comparisons, disease stability on

TE D

appropriate therapy resulted in significantly higher mean HUS (p<0.002-0.02) than when disease was progressing (mean HUS: EGFR, 0.70; ALK, 0.69; WT NSCLC, 0.66; SCLC, 0.52). When evaluating treatment-related toxicities, significant inverse relationships were

EP

observed between HUS and the severity of fatigue and decreased appetite in the EGFR group. There was also a significant inverse relationship between the total number of clinically

AC C

significant symptoms and HUS, both in EGFR-mutated and WT NSCLC patients. Conclusions: In a North American setting, HUS generated from metastatic lung cancer patients are higher in treated, stable patients carrying driver mutations. This is partially explainable by treatment toxicity and patient symptom differences. Such differences in scores should be considered in economic analyses.

3

ACCEPTED MANUSCRIPT INTRODUCTION Lung cancer is the most frequently diagnosed cancer worldwide and the leading cause of cancer-related mortality [1]. Up to 30-40% of patients present with metastatic disease, and

RI PT

are offered systemic therapy as standard of care. The majority are symptomatic at initial diagnosis, with fatigue, loss of appetite, dyspnea, cough and pain [2]. Epidermal growth factor receptor (EGFR) mutations and echinoderm microtubule-associated protein-like 4 and

SC

anaplastic lymphoma kinase (EML4-ALK) rearrangements are detectable in up to 23% and 6% of lung adenocarcinomas, respectively [3]. These activating mutations play important

M AN U

roles in choice of treatment with targeted agents, response to therapy, and prognosis. The EGFR-targeting tyrosine kinase inhibitors (TKIs) gefitinib, erlotinib and afatinib have demonstrated objective response rates (ORRs) between 56 and 83%, progression-free survival (PFS) of approximately 12 months, and median overall survival (OS) of over 2 years

TE D

[4,5,6], in EGFR-mutated non-small cell lung cancer (NSCLC). In patients developing resistance to these agents and carrying a T790M mutation, osimertinib and rociletinib have shown ORRs between 51 and 59% and PFS between 8 and 13 months [7,8]. Many more

EP

third-generation EGFR TKIs currently are in development. For ALK-driven NSCLC, crizotinib has shown durable ORR of 74% and PFS of 10.9 months [9], while other ALK TKIs such as

AC C

ceritinib and alectinib have shown durable ORRs of 50-60% in treatment-naïve patients and in subjects previously treated with crizotinib [10,11]. These drugs all have favorable side-effect profiles when compared to cytotoxic chemotherapy. While extending OS and PFS is the main goal of treatment, improving symptoms, well-being, and quality of life is an equally important priority [12].

4

ACCEPTED MANUSCRIPT Reporting health utility scores (HUS) is a way to incorporate patient-reported outcomes (PRO) into contemporary trials. Utilities reflect an individual’s preferences for specific health-related outcomes, from 0 (dead) to perfect health (1) [13]. HUS can be used and combined with

RI PT

survival outcomes to generate quality-adjusted life-years (QALYs). Cost per QALY is a standard measurement used for cost-utility analyses of medical interventions.

SC

HUS information in lung cancer patients in a real-world, non-clinical trial setting is very limited [14], especially in subjects with metastatic disease [15]. Mean HUS of 0.76 for stage IV

M AN U

patients, and 0.79 while on chemotherapy, have been reported [16], but prior to knowledge of driver mutations and widespread use of targeted therapies. Treatment response also has been demonstrated to result in utility gain [17]. In patients with advanced EGFR-mutated lung cancer, there is recent evidence showing not only improved progression-free survival (PFS)

TE D

with tyrosine kinase inhibitors (TKIs) over chemotherapy, but also gains in health-related quality of life (HRQoL) [18,19,20]. Mean EQ-5D-derived HUS in patients with ALK-positive lung cancer also were reported in one trial as being significantly higher on crizotinib than on

AC C

EP

chemotherapy (0.82 vs 0.73, p<0.05) [21].

Economic analyses in the treatment of metastatic lung cancer can benefit from real-world health utility values. In this new era of targeted therapies with favorable safety profiles over chemotherapy but with significant cost, HUS are important, specifically within subgroups carrying different molecular alterations and under various treatment-dependent disease states.

5

ACCEPTED MANUSCRIPT MATERIALS AND METHODS

Patients and data extraction

RI PT

From November 2014 through March 2016, a longitudinal cohort study at Princess Margaret Cancer Centre evaluated outpatients with metastatic lung cancer across various disease states. Eligibility was broad: any patient with histologically confirmed lung cancer, able to

SC

provide informed consent, without a significant cognitive deficit was eligible. Language posed no barrier, as the EQ-5D-3L was has been validated in 171 languages [22]. Patients in the

M AN U

thoracic outpatient clinics were screened for eligibility. Due to personnel constraints, when there were multiple patients eligible simultaneously, priority was placed on patients with driver alterations and those previously consented (for longitudinal analysis). Thus, patients with EGFR and ALK driver alterations were enriched through targeted enrolment, while patients with wildtype (WT) NSCLC (i.e., those who did not carry known EGFR mutations or ALK

TE D

rearrangements) and small cell lung cancer (SCLC) were sampled conveniently. Subjects were asked to complete, either electronically or on paper, a demographic survey (date of birth, sex, language, employment status, ethnicity, marital status, highest level of education,

EP

income, smoking status). They also filled the EQ-5D-3L questionnaire with five dimensions

AC C

(mobility, self-care, usual activity, pain or discomfort and anxiety or depression), and a visual analogue scale (VAS) of 0 to 100 rating of health [22]. Furthermore, patients graded the severity of nine disease or treatment-related symptoms using the Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE): diarrhea, constipation, decreased appetite, nausea, vomiting, fatigue, neuropathy, skin rash and hair loss. Once subjects had agreed to participate, they were asked at each subsequent visit to fill the EQ-5D-3L and toxicity data. The values obtained for the five domains of EQ-5D-3L were 6

ACCEPTED MANUSCRIPT reduced to a single utility score based upon a set of Canadian preference weights [23]. Medical records of all patients were reviewed for clinical data, treatments and outcomes (date of diagnosis, stage at diagnosis, histology, Eastern Cooperative Oncology Group [ECOG]

RI PT

performance status at diagnosis of metastatic disease, sites of metastases, all previous and current surgical, radiation and systemic treatments with responses, participation in trials with experimental agents, involvement of the palliative care team). Our objective was to compare

SC

HUS by mutational status, therapy, response to treatment and severity of symptoms reported by patients. The study was approved by the University Health Network institutional review

M AN U

board.

Statistical Analysis

Descriptive summary statistics were reported to describe clinico-demographic variables for each group (EGFR-mutated, ALK-rearranged, WT NSCLC, and SCLC). Bivariate analyses

TE D

were conducted across groups using Chi-square and non-parametric Mann-Whitney U tests. Whenever there was a significant difference among groups, multiple pair-wise comparison post-hoc tests with Bonferroni adjustment were conducted to detect which groups were

EP

significantly different. A bivariate analysis using non-parametric tests was conducted to

AC C

assess the relationship between HUS by mutation and disease/treatment state. States included (but were not limited to): being clinically and radiologically stable on most appropriate therapy (e.g., EGFR tyrosine kinase inhibitors for EGFR-mutated patients; chemotherapy for SCLC patients, etc.), progressive disease regardless of therapy, and observation for non-progressive disease. Because of the longitudinal nature of the study, each patient could be assessed multiple times before changing from one disease/treatment state to another. Therefore, a mean HUS associated with a particular state was calculated for 7

ACCEPTED MANUSCRIPT each patient, and a single patient could contribute to multiple HUS associated with different disease/treatment states. Since the majority of patients in the cohort experienced multiple disease/treatment states, when comparing HUS by two different states within a mutation type,

RI PT

a dependent Wilcoxon Signed Rank test was use to assess patients who had both HUS. In particular, we were interested in comparing the HUS of patients with driver mutations on targeted treatment versus WT NSCLC and SCLC patients treated with chemotherapy, or the

SC

HUS of patients with stable disease versus those with progressive disease. In some cases, when the majority of patients within a subgroup only had one particular disease/treatment

M AN U

state, then an independent Mann Whitney U test was used instead.

Descriptive analyses were performed on the frequency of treatment toxicities for each group and compared through Kruskal-Wallis tests for multigroup comparisons, and pair-wise through Mann U Whitney tests. For the comparisons of individual or total number of clinically

TE D

significant toxicities with HUS, the Spearman correlation was used. As we were interested in the relationship between toxicity and HUS and since multiple ratings for each symptom over time were recorded, the highest toxicity rating and its corresponding HUS were selected for

EP

each patient to capture a broad distribution of toxicity ratings. For each symptom, a box-plot

AC C

was generated to visualize the relationship between symptom rating and HUS. The relationship between the number of clinically significant symptoms and HUS was assessed. First, we defined each symptom with a particular cut-off rating to indicate clinical significance (Supplementary Table 1). We then counted how many clinically significant symptoms each patient had experienced. A box-plot was generated to illustrate such relationship. The analyses of symptoms and HUS were conducted for EGFR and WT NSCLC separately due to

8

ACCEPTED MANUSCRIPT different clinical management and outcomes. Other group comparisons were unachievable due to the small sample size in ALK and SCLC groups.

RI PT

For exploratory multiple regression analyses, general linear models were generated, adjusting for important covariates that were known or putative confounders: age at diagnosis, sex, ethnicity, number of organs involved, presence of central nervous system (CNS) metastasis,

SC

presence of liver metastasis, and months since diagnosis. All p-values <0.05 were considered

AC C

EP

TE D

M AN U

significant. All analyses were conducted using SAS version 9.2.

9

ACCEPTED MANUSCRIPT RESULTS

RI PT

Patients Participation rate was 87.4% among all patients approached in clinic: 475 outpatients with metastatic lung cancer completed at least the baseline demographic and EQ-5D-3L questionnaires, for a total of 1571 assessments. The mean number of encounters per subject

SC

was 3.2 (standard deviation 2.7, range 1-16). Patients completed surveys across the entire

initial diagnosis of lung cancer.

M AN U

disease spectrum, with a median of 12 months and a wide range from 0 to 201 months after

The baseline characteristics of all patients are summarized in Table 1. Among the 475 patients, there were 183 (39%) EGFR-mutated NSCLC, 38 (8%) ALK-rearranged NSCLC, 224 (47%) WT NSCLC, and 30 (6%) extensive stage SCLC. There were expected

TE D

demographic and clinical differences between groups, with greater proportions of never smokers, Asians and adenocarcinoma in patients carrying driver alterations (each p<0.0001).

EP

There was a predominance of women in the EGFR group (p=0.006 for comparison with WT NSCLC). ECOG performance status at initial diagnosis of metastatic disease was worse for

AC C

SCLC patients than for all other groups (p<0.0001). Subjects with EGFR mutations were more likely to have CNS, lung, pleural and bone metastases than WT NSCLC patients (p=0.0030.04), and SCLC patients were more likely to have liver metastases than all other groups (p<0.0001).

Previous treatments and current therapy at baseline assessment were also influenced by mutational status, as shown in Table 2. Subjects with WT NSCLC received fewer lines of systemic therapy than all other groups (p<0.0001). The majority of patients with driver 10

ACCEPTED MANUSCRIPT mutations were on targeted agents at the first assessment, while more patients with WT NSCLC and SCLC were on chemotherapy or not treated (p<0.0001). Finally, patients with SCLC were less likely to have had previous surgery (p=0.02), patients with ALK-rearranged

RI PT

tumors were more likely to be treated with an investigational agent as part of a clinical trial (p=0.01), and subjects with EGFR-mutated tumors were less likely to be followed by a

SC

palliative care physician (p=0.03).

M AN U

Health utility scores

Mean HUS according to mutational status, current therapy and response to treatment are shown in Table 3. Intra-individual utility variability (measured as coefficients of variation) averaged 10-12% in various disease states. We compared HUS of patients stable on appropriate treatment across the four groups. Patients with driver mutations stable while

TE D

receiving EGFR and ALK tyrosine kinase inhibitors (TKIs), had higher mean HUS (0.81 ± 0.02 and 0.82 ± 0.02 respectively) than WT NSCLC patients stable on chemotherapy (0.78 ± 0.01,

EP

p=0.04). The difference between patients with driver mutations stable on TKIs and SCLC patients stable on chemotherapy had a non-significant trend (0.72 ± 0.04, p=0.06). In

AC C

mutation-specific comparisons, disease stability on appropriate therapy resulted in significantly higher mean HUS than disease progression (HUS 0.70 ± 0.02 for EGFR, 0.69 ± 0.05 for ALK, 0.66 ± 0.02 for WT NSCLC; p=0.002-0.02). For SCLC patients, there was only a trend, with HUS 0.52 ± 0.08 when progressing (p=0.07). In multivariable analyses, after adjusting for age at diagnosis, sex, ethnicity, number of organs involved, presence of CNS metastasis, presence of liver metastasis, and months since diagnosis, all these differences remained significant. WT NSCLC patients with stable disease on immunotherapy had mean 11

ACCEPTED MANUSCRIPT utilities of 0.80 ± 0.03. In patients with clinically stable disease not receiving any treatment and in those newly diagnosed, mutation status did not affect mean utility values. When looking at mean HUS in patients on specific TKIs, there were no significant differences

RI PT

between first, second or third generation agents.

SC

Longitudinal HUS

Most patients had multiple assessments over time, at various moments of their disease and

M AN U

treatment course. Figure 1 shows longitudinal HUS for selected patients. HUS seemed to correlate well over time with patient’s state, with low values at diagnosis, improvement with palliative radiation or start of systemic therapy, consistent stable values when one was stable

TE D

on treatment, and rapid decline during disease progression.

Treatment toxicities and symptoms

EP

The frequency and mean severity for nine common treatment-related toxicities (some of which may also represent disease symptoms) in each group are presented in

AC C

Supplementary Tables 2 and 3. The data reflect only individuals receiving their optimal therapies: appropriate TKI therapy for EGFR and ALK cancers, and chemotherapy for WT NSCLC and SCLC. The frequencies of each symptom/toxicity were similar across groups (p>0.05, all comparisons). However, mean severities of symptom/toxicities were higher for WT NSCLC than patients with EGFR mutations for decreased appetite, nausea, vomiting, and fatigue, in univariable analyses (p=0.002, each comparison). Patients on ALK TKIs had borderline higher mean severity of vomiting when compared to patients on EGFR TKIs 12

ACCEPTED MANUSCRIPT (p=0.045). Among patients receiving chemotherapy, WT NSCLC patients had higher mean severity of nausea then SCLC patients (p=0.04). In contrast, skin rash mean severity was significantly higher in patients carrying EGFR mutations on EGFR TKIs, than in any other

RI PT

group receiving optimal treatment (p=0.04 to p=0.002, pairwise comparisons). However, in multiple linear regression analyses comparing severity of symptoms/toxicities between groups, no significant differences were found with these individual symptoms/toxicities after

SC

adjustment for age at diagnosis, sex, ethnicity, number of organs involved, presence of CNS metastasis, presence of liver metastasis, and months since diagnosis (Supplementary Table

M AN U

4).

We also dichotomized each individual symptom/toxicity into whether the symptoms were considered clinically significant or not, on the basis of the symptom severity (Supplementary Table 1). We then added the total number of clinically significant symptoms/toxicities, which

TE D

was similar in patients with WT NSCLC and SCLC on chemotherapy, when compared to

EP

EGFR/ALK patients receiving TKI therapy (p=0.28).

Treatment toxicities and health utility scores

AC C

There were too few patients in the ALK-rearranged NSCLC and SCLC groups to evaluate relationships between toxicities and HUS; thus, comparisons were performed only within the EGFR-mutated and WT NSCLC groups (Supplementary Figure 1). We identified significant inverse relationships between the severity of fatigue and HUS (p<0.0001; rho-0.49) and between the severity of decreased appetite and HUS (p=0.004; rho-0.27) in patients carrying EGFR mutations in univariable analyses; results remained highly significant in multiple linear

13

ACCEPTED MANUSCRIPT regression analyses (p<0.0001). No significant associations were found between individual symptoms/toxicities and HUS in the WT NSCLC group. When comparing the total number of clinically significant toxicities, we again only evaluated

RI PT

the subset of patients with EGFR mutations on EGFR TKIs, and separately the subset of WT NSCLC patients receiving chemotherapy (Supplementary Figure 2). In the EGFR group, there was a significant inverse relationship between the total number of clinically significant

SC

symptoms and HUS (p=0.016; rho-0.23), but in the WT NSCLC group, this relationship was borderline (p=0.055; rho-0.20). The strengths of associations were greater after adjustment

M AN U

for age at diagnosis, sex, ethnicity, number of organs involved, presence of CNS metastasis, presence of liver metastasis, and months since diagnosis (respectively: p <0.0001 for EGFR and p=0.0007 for WT NSCLC).

We also explored the relationship between the total number of clinically significant toxicities

TE D

and each of three subdomains of the EQ5D-3L that generated the HUS: anxiety/depression, pain/discomfort, and functional status (sum of values of self-care, mobility, and usual activities), for each group. In the EGFR group, there was only a significant relationship

EP

between the total number of clinically significant symptoms and the anxiety/depression score (p=0.001; rho=0.30) in the univariable analysis; however, in the multiple linear regression

AC C

analysis, this relationship was not significant (p=0.11). In WT NSCLC patients, there were no relationships with specific subdomains.

14

ACCEPTED MANUSCRIPT DISCUSSION In this cohort of outpatients with metastatic lung cancer, we obtained real-world health utility scores (HUS), which were comparable to the values obtained in previous publications. For

RI PT

patients with WT NSCLC on chemotherapy, the HUS was 0.78 in our cohort versus 0.79 in literature [16]. For patients with ALK rearrangements on crizotinib, the HUS was 0.82 in this study, which was similar in a previously reported trial [22]. We demonstrated that mean HUS

SC

are influenced by mutational status and disease state. Confirming the validity and clinical applicability of our HUS, in all groups regardless of mutational status, stability on treatment

M AN U

generated higher HUS than progression. Most importantly, patients with driver mutations who were stable on targeted agents reported higher HUS than WT NSCLC patients on chemotherapy, with a difference of mean HUS scores between 0.04 and 0.05. The minimal clinically important difference (MCID) in EQ-5D utility in lung cancer has previously been estimated at 0.07 to 0.08 [24], but we believe that in our trial with the small number of

TE D

patients, our statistical differences between the groups were also clinically meaningful. In our population, longitudinal HUS for each individual correlated well with their clinical state. For some patients, we documented that HUS dropped even before the diagnosis of progressive

AC C

EP

disease was proven with imaging.

We also identified significant inverse relationships between HUS and the severity of treatment-related toxicities, such as fatigue and decreased appetite in the EGFR group. We suspect that for the WT NSCLC patients, multiple differing symptoms/toxicities affected the HUS, while the relatively few number and severity of symptoms/toxicities observed in the EGFR-mutated patients allowed the relationships between fatigue or decreased appetite and HUS to be discovered. There is evidence of the accumulation of symptoms/toxicities as a 15

ACCEPTED MANUSCRIPT driver of HUS, as there was also a significant inverse relationship between the total number of clinically significant symptoms and HUS, both in EGFR-mutated NSCLC and WT NSCLC patients. We theorize that we would have seen similar relationships in the ALK-rearranged

RI PT

and SCLC patients too, had we obtained larger number of patients for these two disease subgroups.

SC

We measured HUS through the EQ-5D-3L, as no Canadian-derived HUS values were available for the EQ-5D-5L tool. The EQ-5D-3L is an indirect method of measuring HUS, but

M AN U

this tool was chosen to allow us to compare HUS values generated in lung cancer with HUS generated for other cancers and in the non-cancer setting. The ease of using such a tool also allowed us to have high recruitment rates, and high retention rates for the longitudinal portion of this study. By comparing mean HUS with various health states and symptoms/toxicities, we

TE D

have demonstrated the validity of using EQ-5D-3L HUS values in lung cancer patients.

Our study has a number of potential limitations. Firstly, we do not have information on the patients that declined to complete the survey (12.6% of patients approached). Potentially,

EP

they might be more likely to be progressing and to report lower HUS; however, since we

AC C

reported our data by disease state, this likely would result in having no effect on our conclusions, but possibly an over-estimation of HUS in patients who have disease progression. Secondly, the majority of surveys were consistently administered before seeing the physician, but not always, and we did not collect formal information on the timing of surveys relative to physician contact. Filling the survey after discussing investigations and results might have influenced the responses. Also, we enriched enrollment for patients with EGFR and ALK alterations to increase our sample size and allow comparisons between 16

ACCEPTED MANUSCRIPT different groups. Since our institution is a reference centre with expertise and multiple clinical trial options for patients with driver mutations, they are more likely to have survived multiple previous lines of treatment, explaining some of the differences in the baseline characteristics

RI PT

compared to WT NSCLC and SCLC patients. Our sample was small for the ALK and SCLC groups, which limited some of the analyses related to these subsets of patients. As a single institution in Canada, the ability to generalize may be somewhat limited. In Supplementary

SC

Table 5, we provide the HUS values based on UK and US conversions for Table 3.

M AN U

In this single-institution cohort study, patients with metastatic lung cancer carrying driver mutations stable on TKIs reported higher HUS than WT NSCLC and SCLC patients stable on chemotherapy. There were also inverse relationships between treatment-related toxicities and HUS, both in EGFR-mutated NSCLC and WT NSCLC patients, the other two groups being too small to make any conclusions. For patients with driver mutations, targeted agents have

TE D

previously been shown to confer higher ORRs and PFS over chemotherapy, with better safety profile, but with increased cost. Pharmacoeconomic analyses of upcoming therapies should incorporate real-word HUS, which should be specific for different molecular alterations under

AC C

EP

treatment-dependent disease states.

17

ACCEPTED MANUSCRIPT REFERENCES

AC C

EP

TE D

M AN U

SC

RI PT

1. Ferlay J, Soerjomataram I, Ervik M, et al. GLOBOCAN 2012 v1.0, Cancer Incidence and Mortality Worldwide: IARC CancerBase No. 11. Lyon, France: International Agency for Research on Cancer; 2013. Available online: http://globocan.iarc.fr. 2. Cheng L, Alexander RE, MacIennan GT, et al. Molecular pathology of lung cancer: key to personalized medicine. Mod Pathol 25:347-369; 2012. 3. Maemondo M, Inoue A, Kobayashi K, et al. Gefitinib or chemotherapy for non-smallcell lung cancer with mutated EGFR. N Engl J Med 362:2380-2388; 2010. 4. Zhou C, Wu YL, Chen G, et al. Erlotinib versus chemotherapy as first-line treatment for patients with advanced EGFR mutation-positive non-small cell lung cancer (OPTIMAL, CTONG-0802): a multicentre, open-label, randomised, phase 3 study. Lancet Oncol 12:735-742; 2011. 5. Sequist LV, Yang JC, Yamamoto N, et al. Phase III study of afatinib or cisplatin plus pemetrexed in patients with metastatic lung adenocarcinoma with EGFR mutations. J Clin Oncol 31:3327-3334; 2013. 6. Janne PA, Yang JC, Kim DW, et al. AZD9291 in EGFR inhibitor-resistant non-smallcell lung cancer. N Engl J Med 372:1689-1699; 2015. 7. Sequist LV, Soria JC, Goldman JW, et al. Rociletinib in EGFR-mutated non-small-cell lung cancer. N Engl J Med 372:1700-1709; 2015. 8. Solomon BJ, Mok T, Kim DW, et al. First-line crizotinib versus chemotherapy in ALKpositive lung cancer. N Engl J Med 371:2167-2177; 2014. 9. Shaw AT, Kim DW, Mehra R, et al. Ceritinib in ALK-rearranged non-small-cell lung cancer. N Engl J Med 370:1189-1197; 2014. 10. Ou SH, Ahn JS, De Petris L, et al. Alectinib in crizotinib-refractory ALK-rearranged non-small-cell lung cancer: a phase II global study. J Clin Oncol 34:661-668; 2016. 11. Ellis, LM, Bernstein, DS, Voest, EE, et al. American Society of clinical Oncology Perspective: Raising the Bar for Clinical Trials by Defining Clinically Meaningful Outcomes. J Clin Oncol 32: 1277-1280; 2014. 12. Whitehead SJ, Ali S. Health outcomes in economic evaluation: the QALY and utilities. Br Med Bull 96:5-21; 2010. 13. Earle, CC, Chapman, CS, Baker, CM, et al. Systematic Overview of Cost-Utility Assessments in Oncology. J Clin Oncol 18: 3302-3317; 2000. 14. Trippoli S, Vaiani M, Lucioni C, et al. Quality of Life and Utility in Patients with NonSmall Cell Lung Cancer. PharmacoEconomics 19: 855-863; 2001. 15. Tramontano AC, Schrag, DL, Malin, JK, et al. Catalog and Comparison of Societal Preferences (Utilities) for Lung Cancer Health States: Results from the Cancer Care Outcomes Research and Surveillance (CanCORS) Study. Med Decis Making 35: 371387; 2015. 16. Doyle S, Lloyd A, Walker M. Health state utility scores in advanced non-small cell lung cancer. Lung Cancer 62: 374-380; 2008. 18

ACCEPTED MANUSCRIPT

AC C

EP

TE D

M AN U

SC

RI PT

17. Oizumi S, Kobayashi K, Inoue A, et al. Quality of Life with Gefitinib in Patients with EGFR-Mutated Non-Small Cell Lung Cancer: Quality of Life Analysis of North East Japan Study Group 002 Trial. Oncologist 17:863-870; 2012. 18. Chen G, Feng J, Zhou C, et al. Quality of Life (QoL) analyses from OPTIMAL (CTONG-0802), a phase III, randomised, open-label study of first-line erlotinib versus chemotherapy in patients with advanced EGFR mutation-positive non-small cell lung cancer (NSCLC). Ann Oncol 24: 1615-1622; 2013. 19. Griebsch I, Palmer M, Fayers PM, et al. Is progression-free survival associated with a better health-related quality of life in patients with lung cancer? Evidence from two randomised trials with afatinib. BMJ Open; 2014 Oct 31; 4(10):e005762. doi: 10.1136/bmjopen-2014-005762. 20. Geater SL, Xu CR, Zhou C. Symptom and Quality of Life Improvement in LUX-Lung 6 – An Open- Label Phase III Study of Afatinib Versus Cisplatin/Gemcitabine in Asian Patients with EGFR Mutation-Positive Advanced Non-small cell Lung Cancer. J Thorac Oncol 10: 883-889; 2015. 21. Blackhall F, Kim DW, Besse B. Patient-Reported Outcomes and Quality of Life in PROFILE 1007: A Randomized Trial of Crizotinib Compared with Chemotherapy in Previously Treated Patients with ALK-Positive Advanced Non-Small-Cell Lung Cancer. J Thorac Oncol 9: 1625-1633; 2014. 22. The EuroQol Group. EQ-5D-3L: A Measure of Health-Related Quality of Life Developed by the EuroQol Group: User Guide. Version 4.0, April 2011. Rotterdam: The EuroQol Group, 2011. 23. Bansback N, Tsuchiya A, Brazier J, et al. Canadian valuation of EQ-5D health states: preliminary value set and considerations for future valuation studies. PLoS One 2012; 7(2):e31115. doi: 10.1371/journal.pone.0031115. Epub 2012 Feb 6. 24. Pickard AS, Neary MP, Cella D. Estimation of minimally important differences in EQ5D utility and VAS scores in cancer. Health Qual Life Outcomes 5: 70; 2007.

19

ACCEPTED MANUSCRIPT FIGURE LEGENDS

M AN U

SC

RI PT

Figure 1 – Longitudinal health utility scores for selected patients. A. A patient with EGFR-mutated NSCLC, initially with PR on gefitinib, then PD (thin arrow), then started on osimertinib (thick arrow), with PR. B. A patient with ALK-driven NSCLC, with PR on ceritinib. C. A patient with ALK-driven NSCLC, initially with PD on pemetrexed, then started on ceritinib (arrow), with PR. D. A patient with WT NSCLC, initially with SD on pemetrexed, then PD (thin arrow). Treated with palliative radiation (*), then started on docetaxel (thick arrow), with SD. E. A patient with WT NSCLC, with SD on nivolumab. F. A patient with newly diagnosed extensive SCLC, started on chemotherapy (thick arrow). After receiving 4 cycles, had PCI (*), then was on surveillance with SD. ALK: anaplastic lymphoma kinase; EGFR: epidermal growth factor receptor; HUS: health utility score; NSCLC: non-small cell lung cancer; PCI: prophylactic cranial irradiation; PD: progressive disease; PR: partial response; SCLC: small cell lung cancer; SD: stable disease; WT: wildtype.

TE D

Supplementary Figure 1 - Association between individual treatment toxicities and health utility score. Only WT NSCLC and EGFR-mutated NSCLC had large enough sample sizes to complete this analysis. EGFR: epidermal growth factor receptor; NSCLC: non-small cell lung cancer; WT: wildtype.

AC C

EP

Supplementary Figure 2 - Association between number of clinically significant treatment toxicities and health utility score. Only WT NSCLC and EGFR-mutated NSCLC had large enough sample sizes to complete this analysis. EGFR: epidermal growth factor receptor; NSCLC: non-small cell lung cancer; WT: wildtype.

20

ACCEPTED MANUSCRIPT Table 1 – Baseline patient characteristics Characteristics

Median age (range), years, at diagnosis

&

All (n=475) No (%) 64 (29-96)

EGFR (n=183) No (%) 64 (29-96)

ALK (n=38) No (%) 60 (36-85)

WT NSCLC (n=224) No (%) 65 (32-91)

SCLC (n=30) No (%) 66 (44-91)

p value

0.06

AC C

EP

TE D

M AN U

SC

RI PT

Female sex 263 (55) 118 (64) 18 (47) 113 (50) 14 (47) 0.02† Ethnicity White/Caucasian 278 (58) 61 (33) 16 (42) 174 (77) 27 (90) <0.0001§ 160 (34) 102 (56) 20 (53) 35 (16) 3 (10) Asian Other* 37 (8) 20 (11) 2 (5) 15 (7) 0 Never smokers 195 (41) 127 (69) 32 (84) 35 (16) 1 (3) <0.0001§ Histology Adenocarcinoma 385 (81) 177 (97) 37 (97) 171 (76) 0 <0.0001§ Other** 90 (19) 6 (3) 1 (3) 53 (24) 30 (100) TNM stage at diagnosis I-III 119 (25) 40 (22) 7 (18) 67 (30) 5 (17) 0.12 IV 356 (75) 143 (78) 31 (82) 157 (70) 25 (83) ECOG performance status at diagnosis of stage IV disease 0 160 (34) 63 (34) 13 (35) 81 (36) 3 (10) <0.0001¶ 1 261 (55) 110 (61) 23 (62) 115 (51) 13 (43) ≥2 53 (11) 10 (5) 1 (3) 28 (13) 14 (47) Number of organs involved, including lung 3 (10) 0.06 1 53 (11) 15 (8) 5 (13) 30 (13) 200 (42) 73 (40) 16 (42) 104 (47) 7 (23) 2 20 (67) ≥3 222 (47) 95 (52) 17 (45) 90(40) Sites of metastases at any time 73 (33) 12 (40) 0.04† CNS 187 (39) 84 (46) 18 (47) 112 (61) 18 (47) 104 (46) 11 (37) 0.01† Lung 230 (48) 50 (22) 5 (17) 0.003† 136 (7) 69 (38) 12 (32) Pleura <0.0001¶ 2 (5) 33 (15) 14 (47) Liver 79 (17) 30 (16) 10 (33) 0.01† 198 (42) 93 (51) 15 (39) 80 (36) Bone 15 (8) 5 (13) 35 (16) 7 (23) 0.05 Adrenal 62 (13) & At time of first EQ5D assessment (unless otherwise specified). *Black/African Canadian (n=7), Caribbean (n=10), Hispanic/Latino (n=9), Arab/Middle Eastern (n=5), other (n=6). **Squamous carcinoma (n=29), adenosquamous carcinoma (n=10), unclassifiable NSCLC (n=21), SCLC (n=30). †EGFR is significantly different from WT NSCLC. §EGFR and ALK are significantly different from WT NSCLC and SCLC. ¶SCLC is significantly different from EGFR, ALK and WT NSCLC. ALK: anaplastic lymphoma kinase; CNS: central nervous system; ECOG: Eastern Cooperative Oncology Group; EGFR: epidermal growth factor receptor; NSCLC: non-small cell lung cancer; SCLC: small cell lung cancer; TNM: tumor node metastasis; WT: wildtype.

ACCEPTED MANUSCRIPT Table 2 – Previous and current treatments at time of first assessment ALK (n=38) No (%) 18 (0-201)

WT NSCLC (n=224) No (%) 10 (0-173)

SCLC (n=30) No (%) 4 (0-69)

p value

155 (33) 200 (42) 120 (25)

33 (18) 93 (51) 57 (31)

9 (24) 14 (37) 15 (39)

107 (48) 72 (32) 45 (20)

6 (20) 21 (70) 3 (10)

<0.0001*

91 (19) 153 (32) 13 (3) 216 (45) 2 (<1)

14 (8) 122 (67) 1 (<1) 45 (25) 1 (<1)

4 (11) 21 (55) 0 13 (34) 0

59 (26) 10 (5) 11 (5) 143 (64) 0

14 (47) 0 1 (3) 15 (50) 0

<0.0001§

187 (39) 71 (15) 216 (46)

96 (52) 42 (23) 45 (25)

21 (55) 4 (11) 13 (34)

57 (25) 24 (11) 143 (64)

13 (43) 2 (7) 15 (50)

0.27**

128 (27) 258 (54) 52 (11) 75 (16)

49 (27) 96 (52) 25 (14) 19 (10)

10 (26) 23 (61) 9 (24) 5 (13)

68 (30) 124 (55) 17 (8) 47 (21)

1 (3) 15 (50) 1 (3) 4 (13)

0.02¶ 0.76 0.01‡ 0.03†

RI PT

EGFR (n=183) No (%) 18 (0-128)

SC

Median time since diagnosis in months (range) Lines of palliative systemic therapy 0 1 ≥2 Current treatment Chemotherapy Targeted therapy Immunotherapy None Other Response to treatment Not currently progressing Progressing Not currently on treatment Other treatments Any previous surgery Previous palliative radiotherapy Current clinical trial Palliative care team involvement

All (n=475) No (%) 12 (0-201)

M AN U

Characteristics

0.0007

AC C

EP

TE D

*WT NSCLC is significantly different from EGFR, ALK and SCLC. §EGFR and ALK are significantly different from WT NSCLC and SCLC. **Compares only patients on treatment. ¶SCLC is significantly different from EGFR, ALK and WT NSCLC. ‡ ALK is significantly different from WT NSCLC. †EGFR is significantly different from WT NSCLC. ALK: anaplastic lymphoma kinase; EGFR: epidermal growth factor receptor; NSCLC: non-small cell lung cancer; SCLC: small cell lung cancer; WT: wildtype.

ACCEPTED MANUSCRIPT Table 3 – Mean health utility scores according to mutational status and treatment/disease state¶ ALK Mean HUS ± SE 0.82 ± 0.02 (n=30)

Gefitinib 0.80 ± 0.02 (n=71)

Crizotinib 0.81 ± 0.02 (n=19)

Erlotinib 0.81 ± 0.04 (n=7)

Ceritinib 0.83 ± 0.05 (n=10)

Afatinib 0.78 ± 0.08 (n=4)

Brigatinib 0.77 ± 0.22 (n=3)

Clinically stable disease not on treatment Stable on other systemic treatments^ At diagnosis prior to systemic therapy initiation

0.80 ± 0.05 (n=8) 0.76 ± 0.02 (n=17) 0.80 ± 0.13 (n=24)

EP

Progressing

0.69 ± 0.05** (n=15) NA

TE D

Stable on immunotherapy

EGF816 0.84 ± 0.05 (n=8) 0.70 ± 0.02* (n=81) NA

M AN U

Osimertinib 0.84 ± 0.04 (n=14) Rociletinib 0.78 ± 0.04 (n=8)

WT NSCLC Mean HUS ± SE 0.78 ± 0.01‡ (n=75)

SCLC Mean HUS ± SE 0.72 ± 0.04 (n=15)

RI PT

Stable on most appropriate treatment†

EGFR Mean HUS ± SE 0.81 ± 0.02 (n=112)

SC

Disease state

0.73 ± 0.11 (n=5) 0.78 ± 0.08 (n=5) 0.81 ± 0.05 (n=5)

0.66 ± 0.02§ (n=100) 0.80 ± 0.03 (n=14) 0.79 ± 0.02 (n=70) 0.64 ± 0.08 (n=10) 0.76 ± 0.03 (n=56)

0.52 ± 0.08 (n=13) NA 0.69 ± 0.03 (n=13) NA 0.53 ± 0.10 (n=3)

AC C

¶Each patient may contribute to multiple disease states. †Tyrosine kinase inhibitors (TKIs) for EGFR and ALK; chemotherapy for WT NSCLC and SCLC. # ‡p=0.04 (unadjusted) and p=0.01 (adjusted) for comparison of WT NSCLC versus EGFR and ALK. *p=0.004 (unadjusted) and p<0.0001 (adjusted)# for comparison between progressing and stable on most appropriate treatment in EGFR-positive patients. **p=0.002 (unadjusted) and p=0.01 (adjusted)# for comparison between progressing and stable on most appropriate treatment in ALK-positive patients. # § p=0.02 (unadjusted) and p=0.02 (adjusted) for comparison between progressing and stable on most appropriate treatment in WT NSCLC patients. ^Typically the treatment would be chemotherapy in EGFR or ALK mutated patients or molecularly targeted therapy in wildtype patients. #Adjusted for age at diagnosis, sex, ethnicity, number of organs involved, presence of central nervous system (CNS) metastasis, presence of liver metastasis, and months since diagnosis. ALK: anaplastic lymphoma kinase; EGFR: epidermal growth factor receptor; HUS: health utility score; NSCLC: non-small cell lung cancer; SCLC: small cell lung cancer; SE: standard error; WT: wildtype.

ACCEPTED MANUSCRIPT Supplementary Table 1 – Individual PRO-CTCAE symptom/toxicity severity score definitions* Symptom

Severity Score 2

3

4

5

Diarrhea

Never

Rarely

Occasionally

Frequently

Vomiting

Never

Rarely

Occasionally

Frequently

Constipation

None

Mild

Moderate

Severe

Almost constantly Almost constantly Very severe

Decreased appetite

None

Mild

Moderate

Severe

Very severe

Nausea

None

Mild

Moderate

Severe

Very severe

RI PT

1

None

Mild

Moderate

Severe

Very severe

Neuropathy

None

Mild

Moderate

Severe

Very severe

No

Yes, asymptomatic

EP

TE D

M AN U

Yes, with Yes, with symptoms of symptoms, pruritus or interfering pain, but with daily life tolerable Hair loss No Yes, <50 % of Yes, ≥50 % of the hair the hair *The shaded areas represent the symptom scores that are above the cut-point, and therefore are considered relevant symptoms and have value on the final relevant toxicity score. PRO-CTCAE: Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Event

AC C

Skin rash

SC

Fatigue

ACCEPTED MANUSCRIPT Supplementary Table 2 – Percentage of patients with any level of symptom/toxicity (by PRO-CTCAE) EGFR (n=112) 90

ALK (n=30) 83

WT NSCLC (n=75) 85

SCLC (n=15) 66

p value

Constipation

89

83

85

66

0.13

Decreased appetite Nausea Vomiting

89 89 90

83 83 86

83 90 85

66 66 66

0.16 0.12 0.16

Fatigue Neuropathy

89 89

83 83

86 85

73 73

Diarrhea

0.13

RI PT

Symptom

0.09 0.38

AC C

EP

TE D

M AN U

SC

Skin rash 90 83 85 66 0.10 Hair loss 90 83 85 66 0.07 ALK: anaplastic lymphoma kinase; EGFR: epidermal growth factor receptor; NSCLC: non-small cell lung cancer; PROCTCAE: Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events; SCLC: small cell lung cancer; WT: wildtype.

ACCEPTED MANUSCRIPT Supplementary Table 3 – Mean severity of symptoms/toxicities using PRO-CTCAE

WT NSCLC SCLC p value EGFR ALK (n=112) (n=30) (n=75) (n=15) Mean ± SD Mean ± SD Mean ± SD Mean ± SD Diarrhea 2.33 ± 1.02 2.29 ± 1.03 2.36 ± 1.05 1.92 ± 0.09 0.48 Constipation 2.06 ± 0.91 2.41 ± 1.11 2.44 ± 1.13 2.23 ± 1.24 0.77 † Decreased appetite 2.05 ± 0.88 2.25 ± 1.13 2.58 ± 1.13 2.04 ± 1.12 0.02 § Nausea 1.84 ± 0.71 2.26 ± 1.17 2.28 ± 1.05 1.76 ± 0.84 0.01 ‡ Vomiting 1.68 ± 0.50 2.08 ± 0.91 2.09 ± 0.93 2.09 ± 0.66 0.01 † Fatigue 2.33 ± 0.96 2.48 ± 1.06 2.89 ± 1.25 2.61 ± 1.23 0.02 Neuropathy 1.91 ± 0.73 1.99 ± 0.85 2.09 ± 0.81 1.83 ± 0.84 0.43 * ¶ Skin rash 2.29 ± 0.91 1.90 ± 0.67 1.93 ± 0.72 1.82 ± 0.88 0.02 ** Hair loss 1.90 ± 0.71 1.79 ± 0.70 2.09 ± 0.87 2.54 ± 1.29 0.05 †EGFR is significantly different from WT NSCLC. §WT NSCLC is significantly different from EGFR and SCLC. ‡ EGFR is significantly different from ALK and WT NSCLC. ¶ EGFR is significantly different from ALK, WT NSCLC and SCLC. *This symptom was scored from 1-4 only. **This symptom was scored from 1-3 only. ALK: anaplastic lymphoma kinase; EGFR: epidermal growth factor receptor; NSCLC: non-small cell lung cancer; PROCTCAE: Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events; SCLC: small cell lung cancer; SD: standard deviation; WT: wildtype.

AC C

EP

TE D

M AN U

SC

RI PT

Symptom (1-5)

ACCEPTED MANUSCRIPT Supplementary Table 4 – Adjusted p values for pair-wise comparisons of mean severity of symptoms/toxicities*

WT NSCLC EGFR EGFR EGFR ALK ALK vs vs vs vs vs vs SCLC WT NSCLC SCLC WT NSCLC SCLC ALK Decreased appetite 0.27 0.15 0.87 0.93 0.46 0.93 Nausea 0.66 0.28 0.63 0.41 0.14 0.41 Vomiting 0.06 0.10 0.97 0.60 0.30 0.60 Fatigue 0.18 0.095 0.61 0.97 0.75 0.97 Skin rash 0.91 0.33 0.26 0.51 0.33 0.51 Hair loss 0.65 0.22 0.17 0.67 0.29 0.67 *Adjusted for age at first diagnosis, sex, ethnicity, number of organs involved, presence of central nervous system (CNS) metastasis, presence of liver metastasis and months since diagnosis. ALK: anaplastic lymphoma kinase; EGFR: epidermal growth factor receptor; NSCLC: non-small cell lung cancer; SCLC: small cell lung cancer; WT: wildtype.

AC C

EP

TE D

M AN U

SC

RI PT

Symptoms

ACCEPTED MANUSCRIPT Supplementary Table 5 – UK and US conversions for mean health utility scores according to mutational status and treatment/disease state¶

Stable on immunotherapy Clinically stable disease not on treatment Stable on other systemic treatments^ At diagnosis prior to systemic therapy initiation

UK US UK US UK US UK US UK US UK US

ALK Mean HUS ± SE 0.73 ± 0.05 0.79 ± 0.03 0.65 ± 0.07 0.74 ± 0.05 NA NA 0.78 ± 0.16 0.84 ± 0.11 0.73 ± 0.09 0.79 ± 0.07 0.81 ± 0.05 0.85 ± 0.04

WT NSCLC Mean HUS ± SE 0.73 ± 0.03 0.79 ± 0.02 0.55 ± 0.03 0.67 ± 0.02 0.73 ± 0.05 0.79 ± 0.04 0.76 ± 0.03 0.81 ± 0.02 0.52 ± 0.12 0.63 ± 0.08 0.77 ± 0.03 0.83 ± 0.02

SCLC Mean HUS ± SE 0.69 ± 0.06 0.76 ± 0.04 0.37 ± 0.11 0.53 ± 0.08 NA NA 0.54 ± 0.08 0.67 ± 0.05 NA NA 0.62 ± 0.06 0.69 ± 0.05

RI PT

Stable on most appropriate treatment† Progressing

EGFR Mean HUS ± SE 0.77 ± 0.02 0.82 ± 0.01 0.64 ± 0.03 0.73 ± 0.02 NA NA 0.76 ± 0.05 0.81 ± 0.04 0.72 ± 0.04 0.78 ± 0.03 0.79 ± 0.04 0.83 ± 0.03

SC

Disease state

AC C

EP

TE D

M AN U

¶Each patient may contribute to multiple disease states. †Tyrosine kinase inhibitors (TKIs) for EGFR and ALK; chemotherapy for WT NSCLC and SCLC. ^Typically the treatment would be chemotherapy in EGFR or ALK mutated patients or molecularly targeted therapy in wildtype patients. ALK: anaplastic lymphoma kinase; EGFR: epidermal growth factor receptor; HUS: health utility score; NSCLC: non-small cell lung cancer; SCLC: small cell lung cancer; SE: standard error; WT: wildtype.

AC C

EP

TE D

M AN U

SC

RI PT

ACCEPTED MANUSCRIPT

AC C

EP

TE D

M AN U

SC

RI PT

ACCEPTED MANUSCRIPT

AC C

EP

TE D

M AN U

SC

RI PT

ACCEPTED MANUSCRIPT