ABSTRACT
Background
This study aimed to characterize longitudinal trajectories of tumor burden and treatment‐related symptoms following immune checkpoint inhibitor (ICI) therapy in patients with advanced lung cancer, based on electronic patient‐reported outcomes (ePRO).
Methods
Using the MD Anderson Symptom Inventory‐Lung Cancer module and an immune‐related adverse event symptom item scale, we collected the ePRO data of patients undergoing first‐line immunotherapy‐based combination treatment for advanced unresectable primary lung cancer. Evaluating trajectories of primary symptoms and symptom differences between treatment groups using linear mixed‐effects models.
Results
A total of 168 patients were included in the study. The top five symptoms with the highest severity before treatment were coughing, distress, shortness of breath, disturbed sleep, and pain. Coughing was gradually attenuated with ongoing treatment. Symptoms of distress, shortness of breath, disturbed sleep, and pain also showed an overall decreasing trend. The top five immunotherapy‐related symptoms, with the highest severity, were early satiety, abdominal distension, night sweats, altered sense of taste, and bloated pain, which demonstrated a cyclical gradual increase throughout treatment. Compared to the ICIs + chemotherapy group, the ICIs + chemotherapy + VEGFR‐TKIs group showed significantly lower burden in four of the top five immunotherapy‐related symptoms, with the exception of night sweats, which demonstrated no significant difference.
Conclusions
Patients with advanced lung cancer experienced reduced severity of lung cancer‐related symptoms after receiving immunotherapy‐based combination treatment, and immune‐specific symptoms showed cyclical exacerbation with ongoing treatment. The addition of VEGFR‐TKIs to ICIs + chemotherapy did not increase the associated toxicity burden.
Keywords: immunotherapy, lung cancer, patient‐reported outcome, symptom analysis
This study enrolled 168 patients with advanced NSCLC receiving first‐line immunotherapy‐based combination regimens. ePRO data revealed that: (1) Lung cancer‐related symptoms were alleviated post‐treatment; (2) Immunotherapy‐specific symptom burden exhibited cyclical exacerbation; (3) The ICIs + chemotherapy + VEGFR‐TKIs group did not demonstrate additional treatment‐related burden compared to the ICIs + chemotherapy group.
1. Introduction
Lung cancer is a malignant tumor with a high worldwide prevalence [1]. Some patients have advanced disease at the time of their medical consultation, which leads to poor prognosis [2, 3]. In recent years, the use of immune checkpoint inhibitors (ICIs) has considerably improved the survival outcomes of patients with driver‐gene‐negative advanced non‐small‐cell lung cancer (NSCLC) [4, 5, 6]. With a gradual shift toward the management of advanced lung cancer as a chronic disease, patients with this condition have placed increasingly higher demands on their quality of life. However, immunotherapy has only been applied in clinical practice for a relatively short time, and the toxicity of immunotherapy drugs poses clinical challenges, including poor predictability, rapid reactions, and high risk of vital organ involvement [7, 8, 9]. Immune toxicity management mainly involves observation by doctors and nurses during the in‐hospital treatment period. Out‐of‐hospital dynamic data and patient self‐reported data are lacking. This is unfavorable for enhancing the efficiency of comprehensive management and ensuring the quality of life of patients with advanced lung cancer.
A patient‐reported outcome (PRO) refers to direct feedback from a patient regarding their health status, functional status, and treatment experience [10]. Temporal changes in PRO may serve as early indicators of important clinical events, such as tumor progression [11, 12], response evaluation [13, 14], and toxic side effects of drugs [15, 16]. In recent years, PRO‐based disease management has gained increasing attention. Dai et al. [9] performed PRO‐based symptom management after lung cancer surgery and found that patients in the PRO group had better outcomes compared with those in the conventional follow‐up group. PROs have also been applied to the observation of symptoms during chemotherapy in patients with advanced lung cancer [7]. Immunotherapy‐based combination treatment is currently the mainstay of clinical treatment of driver‐gene‐negative advanced lung cancer. However, PRO data on immunotherapy‐based combination treatment and reports on the dynamic and comprehensive trajectories of symptom changes remain limited. Therefore, we employed electronic PROs (ePROs) to observe the changes in symptom distribution and severity before and after the treatment of patients with advanced primary lung cancer undergoing first‐line immunotherapy as basic treatment. Our study hopes to provide fundamental research data for immune toxicity and comprehensive management in advanced lung cancer [17].
2. Methods
This was a prospective, multicentre, observational study initiated by Sichuan Cancer Hospital. Study approval was granted by the ethics committee of the hospital (approval number: SCCHEC‐02‐2022‐068), and the study was registered in the Chinese Clinical Trial Registry (registration number: ChiCTR2200061540). Patients in three tertiary hospitals in China between July 2022 and August 2023 were included as participants.
2.1. Participants
The inclusion criteria were as follows: (1) pathological diagnosis of stage IIIc–IV unresectable primary lung cancer; (2) patients undergoing standard first‐line immunotherapy‐based combination treatment; (3) patients with good cognitive and reading abilities and the ability to complete scales independently; (4) expected survival ≥ 3 months; and (5) Eastern Cooperative Oncology Group Performance Status (ECOG PS) score of 0–2 points. The exclusion criteria were as follows: (1) age < 18 years; (2) patients without internet access or electronic devices; (3) cognitive impairment or inability to understand the study content; (4) inability to cooperate with active symptom reporting during the entire study period; and (5) contraindications to chemotherapy, immunotherapy, or anti‐vascular therapy. The criteria for termination of participation in the study were as follows: (1) disease progression; (2) death or loss to follow‐up; and (3) withdrawal of consent by the participant or their legal representative.
2.2. Data Acquisition
2.2.1. General Data
Patient data, including age, sex, height, body weight, educational level, smoking history, drinking history, pathological type and stage of tumor, and ECOG PS score, were extracted from the electronic medical record system. Comprehensive assessments and decision‐making regarding treatment regimens and medication dosages were performed based on clinical guidelines by professional oncologists.
2.2.2. ePRO Data
PROs were primarily collected through a self‐administered electronic scale. The link or quick‐response code to the electronic scale was sent by the researchers to the patients via messaging services (e.g., WeChat or short message service). After completing the scale independently, the patients uploaded their data to the Research Electronic Data Capture (REDCap) system of Sichuan Cancer Hospital. All patients were required to complete two PRO scales independently, every week before the initiation of immunotherapy‐based combination treatment, until the end of the treatment cycle. Scales were collected at the following five time points during each treatment cycle: before treatment, on the day of treatment, 1 week after treatment, 2 weeks after treatment, and 3 weeks after treatment. The electronic version of the MD Anderson Symptom Inventory‐Lung Cancer module (MDASI‐LC) included 16 common core symptom items associated with lung cancer and its treatment [18]. In addition, the immune‐related adverse event (iRAE) symptom item scale used in this study comprised 15 common immune toxicity symptoms (Table S1 shows the contents of the scales). Each item on the two scales mentioned above was self‐rated on a scale of 0–10 for symptom severity, with 0 indicating an absence of the symptom and 10 indicating the greatest severity the patient could imagine. A self‐reported symptom score ≥ 1 was defined as the presence of symptoms, and a score of ≥ 4 was defined as moderate‐to‐severe symptoms [19, 20]. Prevalence was defined as the percentage of patients with symptom scores ≥ 1 relative to the total patient cohort. The completion rate of the scale referred to the percentage of fully completed scales out of the total number distributed. Post‐treatment toxic side effect‐related symptoms were described in accordance with the Common Terminology Criteria for Adverse Events version 5.0 [21].
2.3. Data Management
The data of the present study were managed using the REDCap system, which is widely used by institutions worldwide [22]. All data were ultimately entered into the project database of the system. The REDCap system was adopted at our hospital in late 2017 and directly installed on the hospital's server (website: http://125.71.214.100:888/redcap).
2.4. Response Evaluation
A treatment cycle was defined as a 3‐week period, based on clinical treatment standards. Starting from the first treatment, patients underwent response evaluation after every two treatment cycles, in accordance with the Response Evaluation Criteria in Solid Tumors version 1.1 [23]. The collected data were used for correlation analysis of the distribution and dynamic changes of symptoms with ongoing treatment.
2.5. Statistical Analysis
Data analysis was performed using SPSS (version 25.0), R (version 4.3.3), and visualization was performed using GraphPad Prism (version 9.0). The general data, clinical characteristics, and symptom distribution of the study population were analyzed using descriptive statistics. Patient age is expressed as median and interquartile range, whereas patient‐reported symptom severity is expressed as mean ± standard deviation. Categorical variables are expressed as numbers, percentages, or proportions. We preliminarily analyzed the prevalence, severity, and proportion of reports of moderate to severe symptom severity in patient‐reported symptoms at each PRO assessment time point during the first and last treatment cycles to describe the changes in symptoms before and after treatment. Subsequently, the top five lung cancer‐related symptoms with the highest baseline severities and the top five immunotherapy‐related symptoms with the highest severities during the first treatment cycle were screened. Between‐group differences in top five symptom scores were assessed using independent t‐tests. Significant variables (p < 0.05) advanced to multivariate linear regression. Linear mixed‐effects models (LMMs) were applied to analyze longitudinal data, assessing changes in top five symptoms over time and comparing symptom trajectories across treatment groups. The models specified symptom mean scores as the dependent variable, with time, treatment group, and the time‐by‐treatment interaction as independent variables. Covariates showing significant intergroup differences were adjusted for in LMMs. All parameters were estimated by maximum likelihood. All symptoms other than coughing exhibited fluctuations during each treatment cycle. Simple linear regression was employed to analyze the presence or absence of linear relationships of symptom peaks and troughs with time, to further analyze the trends of change and cyclical characteristics of the symptoms. For comparisons of other outcomes, categorical variables were analyzed using chi‐square or Fisher's exact tests, while continuous variables were assessed with Student's t‐tests. A two‐sided p‐value of < 0.05 was considered statistically significant.
3. Results
3.1. General Data
A total of 3029 patients were preliminarily screened, and 217 were included in the study after applying the inclusion and exclusion criteria. During the study period, 46 patients experienced disease progression, and 3 were lost to follow‐up. Ultimately, the data of 168 patients were included in our analysis (Figure 1). Table 1 shows the baseline characteristics of the study population.
FIGURE 1.
Flow diagram.
TABLE 1.
Baseline characteristics of the study population (N = 168).
| Characteristic | N | Percentage (%) |
|---|---|---|
| Age (years) | ||
| ≤ 65 | 99 | 58.93 |
| > 65 | 69 | 41.07 |
| Sex | ||
| Male | 150 | 89.29 |
| Female | 18 | 10.71 |
| Pathological type | ||
| Squamous cell carcinoma | 94 | 55.95 |
| Adenocarcinoma | 41 | 24.40 |
| Small cell carcinoma | 31 | 18.45 |
| Large cell carcinoma | 2 | 1.19 |
| Stage | ||
| III | 71 | 42.26 |
| IV | 97 | 57.74 |
| ECOG score | ||
| 0–1 | 151 | 89.88 |
| ≥ 2 | 17 | 10.12 |
| BMI | ||
| < 18.5 | 7 | 4.17 |
| 18.5–24.0 | 104 | 60.91 |
| ≥ 24.0 | 57 | 33.93 |
| Smoking history | ||
| No | 34 | 20.24 |
| Yes | 134 | 79.76 |
| Drinking history | ||
| No | 103 | 61.31 |
| Yes | 65 | 38.69 |
| Family history of tumor | ||
| No | 144 | 85.71 |
| Yes | 24 | 14.29 |
| Treatment | ||
| ICIs + chemotherapy | 134 | 79.76 |
| ICIs + chemotherapy + VEGFR‐TKIs | 34 | 20.24 |
Abbreviations: BMI, body mass index; ECOG, Eastern Cooperative Oncology Group; ICIs, immume checkpoint inhibitors; VEGFR‐TKIs, vascular endothelial growth factor receptor tyrosine kinase inhibitors.
3.2. PRO Scale Completion Rate
The study participants were required to complete the MDASI‐LC module and the iRAE symptom item scale. Table S2 shows the scales completion rates of the various study centres.
3.3. Symptom Distribution
3.3.1. Lung Cancer‐Related Symptoms in the MDASI‐LC
Based on the ePRO data, the main symptoms reported by patients before immunotherapy‐based combination treatment were coughing, shortness of breath, distress, sadness, and disturbed sleep. The most common symptoms reported by patients after undergoing treatment were coughing, fatigue, lack of appetite, shortness of breath, and disturbed sleep (Table S3). The top five symptoms with moderate‐to‐severe severity (≥ 4 points) before treatment and their occurrence rates were coughing (58.93%), distress (24.40%), shortness of breath (22.62%), pain (20.24%), and disturbed sleep (20.24%). Meanwhile, the top five symptoms with moderate‐to‐severe severity after treatment and their occurrence rates were disturbed sleep (19.05%), fatigue (17.86%), difficulty remembering (11.90%), shortness of breath (10.71%), and lack of appetite (10.12%).
3.3.2. Immunotherapy‐Related Symptoms
Symptoms with the highest occurrence rates after the first and last treatment cycles were early satiety, abdominal distension, night sweat, altered sense of taste, and bloated pain. Abdominal distension, night sweat, and bloated pain were most common on the day of treatment, whereas early satiety and an altered sense of taste had the highest occurrence rates 1 week after treatment (Table S4).
3.3.3. Dynamic Changes in Symptoms After Treatment
The occurrence rates and severity of patient‐reported lung cancer‐related symptoms (e.g., pain, shortness of breath, coughing, and sore throat) after treatment decreased compared with the pre‐treatment levels. However, the occurrence rates of patient‐reported toxic side effect‐related symptoms, such as fatigue, nausea, lack of appetite, and vomiting, increased after treatment. For certain symptoms such as palpitation, there was a dissociation between the patient‐reported occurrence rate and severity, that is, the occurrence rate increased but the severity decreased. The top five symptoms with the highest severity before treatment were coughing (3.80 ± 2.34), distressed (2.07 ± 2.14), shortness of breath (1.98 ± 2.18), disturbed sleep (1.77 ± 2.19), and pain (1.64 ± 2.25). Figure 2 shows the dynamic changes in the symptoms. Coughing, which had the highest baseline occurrence rate and severity, showed a trend of gradual attenuation with ongoing immunotherapy‐based combination treatment (p < 0.001). Differences in distressed (p < 0.001), shortness of breath (p < 0.001), disturbed sleep (p = 0.022), and pain (p = 0.001) between various time points were statistically significant. At the last follow‐up, the severities of the symptoms mentioned above had returned to the levels before baseline.
FIGURE 2.
Patient‐reported outcomes of Top 5 symptoms in MDASI‐LC (MD Anderson Symptom Inventory‐Lung Cancer mondule). Error bars are the 95% confidence intervals. Linear mixed‐effect models were used to evaluate whether symptoms significantly differed over time. (C1–6, cycle 1 to cycle 6).
Patient‐reported immunotherapy‐related symptoms, such as bloated pain, night sweat, rash, pruritus, abdominal distension, early satiety, and altered sense of taste, primarily occurred after the start of treatment. They then persisted throughout the entire treatment period, with an increasing trend. The top five symptoms with the highest mean severity scores during the first treatment cycle were early satiety (1.19 ± 1.41), abdominal distension (0.91 ± 1.51), night sweat (0.78 ± 1.28), altered sense of taste (0.60 ± 1.16), and bloated pain (0.60 ± 1.26). Figure 3 depicts the longitudinal changes in the mean symptom scores. The symptoms generally exhibited a gradually increasing trend, with the differences between various time points being statistically significant (p < 0.001).
FIGURE 3.
Patient‐reported outcomes of Top 5 immunotherapy‐related symptom. Error bars are the 95% confidence intervals. Linear mixed‐effect models were used to evaluate whether symptoms significantly differed over time. (C1–6, cycle 1 to cycle 6).
3.3.4. Cyclical Trends of the Top Five Symptoms
We applied simple linear regression modeling to decipher symptom periodicity patterns, providing clinicians with predictive insights for preemptive management of symptom trajectories.
Except for coughing, which exhibited gradual attenuation with ongoing immunotherapy‐based combination treatment, all the symptoms showed fluctuations during each treatment cycle. Scores for shortness of breath and disturbed sleep peaked on the day of treatment during each treatment cycle and decreased to the lowest value before the next treatment cycle. Distressed exhibited a peak value on the day of treatment or 1 week after treatment and troughed before the next treatment cycle. The pain score peaked at 1 week after treatment during each treatment cycle and returned to the lowest level by the third week after treatment or before the next cycle. Simple linear regression (Table 2) revealed that the influence of time on the trough values of the disturbed sleep score was statistically significant (b = 0.009, p = 0.006). This indicates that the disturbed sleep symptom was alleviated after each treatment cycle, but the degree of alleviation gradually decreased with time. A linear relationship existed between time and the trough values of shortness of breath (b = −0.015, p = 0.007), suggesting that shortness of breath was gradually attenuated with ongoing immunotherapy‐based combination treatment.
TABLE 2.
Simple linear regression analysis of time and symptom scores.
| Items | Time | b | SE | β | t | p |
|---|---|---|---|---|---|---|
| Distressed | ||||||
| Peak | W0/W1 | −0.018 | 0.008 | −0.768 | −2.401 | 0.074 |
| Trough | Pretreatment | 0.003 | 0.002 | 0.632 | 1.631 | 0.178 |
| Shortness of breath | ||||||
| Peak | W0 | −0.012 | 0.007 | −0.625 | −1.601 | 0.185 |
| Trough | Pretreatment | −0.015 | 0.003 | −0.929 | −5.011 | 0.007 |
| Disturbed sleep | ||||||
| Peak | W0 | 0 | 0.009 | 0.014 | 0.028 | 0.979 |
| Trough | Pretreatment | 0.009 | 0.002 | 0.935 | 5.256 | 0.006 |
| Pain | ||||||
| Peak | W1 | −0.003 | 0.008 | −0.176 | −0.358 | 0.739 |
| Trough | W3/Pretreatment | −0.007 | 0.003 | −0.694 | −1.926 | 0.126 |
| Early satiety | ||||||
| Peak | W1 | 0.02 | 0.002 | 0.977 | 9.228 | 0.001 |
| Trough | Pretreatment | 0.034 | 0.005 | 0.956 | 6.481 | 0.003 |
| Abdominal distension | ||||||
| Peak | W0/W1 | 0.024 | 0.003 | 0.975 | 8.801 | 0.001 |
| Trough | Pretreatment | 0.03 | 0.006 | 0.936 | 5.32 | 0.006 |
| Night sweat | ||||||
| Peak | W0 | 0.016 | 0.001 | 0.987 | 12.273 | < 0.001 |
| Trough | Pretreatment | 0.018 | 0.002 | 0.97 | 7.976 | 0.001 |
| Altered sense of taste | ||||||
| Peak | W1 | 0.013 | 0.004 | 0.827 | 2.938 | 0.042 |
| Trough | Pretreatment | 0.013 | 0.003 | 0.897 | 4.053 | 0.015 |
| Bloated pain | ||||||
| Peak | W0/W1 | 0.029 | 0.003 | 0.979 | 9.592 | 0.001 |
| Trough | Pretreatment | 0.028 | 0.004 | 0.963 | 7.125 | 0.002 |
Note: Values in bold indicate p‐values < 0.05, signifying statistically significant results.
Abbreviations: SE, standard error; W0, the day of treatment; W1, 1 week after treatment; W3, 3 weeks after treatment.
Among the patient‐reported immunotherapy‐related symptoms, early satiety and altered sense of taste reached their peak scores 1 week after treatment and returned to their lowest levels before the next treatment cycle. Simple linear regression analysis (Table 2) revealed that the influence of time on the peak and trough values of early satiety and altered sense of taste was statistically significant (p < 0.05). The peak score for night sweat appeared on the day of treatment during each treatment cycle, whereas the trough score appeared before the next treatment cycle. A linear relationship existed between time and the peak (p < 0.001) and trough (p = 0.001) values. Both the peak and trough values showed a gradual increase with ongoing treatment. The severity of abdominal distension and bloated pain peaked on the day of treatment or 1 week after treatment during each treatment cycle and gradually returned to the lowest levels before the next treatment cycle. Simple linear regression analysis revealed the presence of a positive linear relationship between time and the peak and trough values of abdominal distension and bloated pain (p < 0.05). In summary, the severity of the top five immunotherapy‐related symptoms exhibited a gradual cyclical increase with ongoing immunotherapy‐based combination treatment.
3.3.5. Subgroup Analysis of Symptom Scores
Independent samples t‐tests compared symptom severity across subgroups stratified by age, sex, ECOG score, stage, and smoking history. Results revealed statistically significant differences (p < 0.05) in all top five symptoms between stage III and IV patients. Most symptoms also varied significantly by smoking history (Table S5). Variables influencing symptom scores in the t‐tests were incorporated into multivariate linear regression models. The analysis demonstrated that stage significantly affected both lung cancer‐related and immunotherapy‐related symptoms (p < 0.001), with stage IV patients exhibiting a higher symptom burden than stage III patients. Current/former smokers reported greater severity of coughing (b = 0.15, t = 2.00, p = 0.046) and night sweat (b = 0.27, t = 6.96, p < 0.001), but lower pain severity (b = −0.22, t = −2.95, p = 0.003) compared to never‐smokers (Table 3). To validate result stability, identical analyses were conducted in the ICIs + chemotherapy subgroup. Consistent findings were replicated (Tables S6 and S7).
TABLE 3.
Multivariate linear regression analysis of stage and smoking history (all patients).
| MDASI‐LC symptoms | ||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Variables | Coughing | Distressed | Shortness of breath | Disturbed sleep | Pain | |||||||||||||||
| b | SE | t | P | b | SE | t | P | b | SE | t | P | b | SE | t | P | b | SE | t | P | |
| Stage a | 0.40 | 0.05 | 7.89 | < 0.001 | 0.40 | 0.05 | 8.61 | < 0.001 | 0.38 | 0.05 | 7.33 | < 0.001 | 0.92 | 0.06 | 16.44 | < 0.001 | 0.78 | 0.05 | 15.98 | < 0.001 |
| Smoking history b | 0.15 | 0.08 | 2.00 | 0.046 | 0.30 | 0.08 | 3.80 | < 0.001 | 0.40 | 0.07 | 5.86 | < 0.001 | −0.22 | 0.07 | −2.95 | 0.003 | ||||
| Immunotherapy‐related symptoms | ||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Variables | Abdominal distension | Night sweat | Altered sense of taste | Bloated pain | ||||||||||||
| b | SE | t | P | b | SE | t | P | b | SE | t | P | b | SE | t | P | |
| Stage a | 0.40 | 0.05 | 8.77 | < 0.001 | 0.35 | 0.04 | 9.79 | < 0.001 | 0.20 | 0.07 | 2.83 | < 0.001 | 0.38 | 0.05 | 8.44 | < 0.001 |
| Smoking history b | 0.37 | 0.05 | 6.96 | < 0.001 | 0.18 | 0.04 | 4.06 | < 0.001 | 0.10 | 0.07 | 1.47 | 0.142 | ||||
Note: Early satiety was found to be influenced solely by stage in the t‐test analysis, so multiple linear regression analysis was not performed for this symptom.
Abbreviations: MDASI‐LC, MD Anderson Symptom Inventory–Lung Cancer module; SE, standard error.
Stage III is the control group.
Patients with a history of smoking is the control group.
3.3.6. Comparison of Symptom Trajectories Between Treatment Groups
Significant baseline differences existed between the ICIs + chemotherapy and ICIs + chemotherapy + vascular endothelial growth factor receptor tyrosine kinase inhibitors (VEGFR‐TKIs) groups in histology (p < 0.001) and smoking history (p = 0.003). No differences were observed in sex, age, ECOG score, stage, BMI, alcohol use, or family history (Table S8). After adjusting for histology and smoking history in linear mixed‐effects models, the ICIs + chemotherapy + VEGFR‐TKIs group demonstrated significantly milder coughing (p = 0.040), shortness of breath (p = 0.003), and disturbed sleep (p < 0.001), lower burden of immunotherapy‐related symptoms including early satiety (p = 0.008), abdominal distension (p = 0.001), altered sense of taste (p < 0.001), and bloated pain (p < 0.001) compared to the ICIs + chemotherapy group. Night sweats showed no intergroup difference (p = 0.113) (Figure 4).
FIGURE 4.
Patient‐reported outcomes of ICIs + chemotherapy versus ICIs + chemotherapy + VEGFR‐TKIs. Error bars are the 95% confidence intervals. (Pre, Pretreatment; C1–C6, Cycle 1 to Cycle 6; W1, 1 Week after treatment).
4. Discussion
In the present study, we used ePRO data to report the distribution of symptoms of patients with advanced primary lung cancer, before and after receiving immunotherapy‐based combination treatment. We also analyzed the longitudinal trajectory characteristics of tumor‐related symptoms and immunotherapy‐related adverse events during the treatment period. Cancer‐related PRO‐based studies have become an emerging focal topic in clinical research on patients with tumors. PROs have already been adopted in clinical trials of immunotherapy for lung cancer [24, 25, 26]. However, these studies have mainly focused on the assessment of disease‐related symptoms and common adverse reactions, with limited analysis of immunotherapy‐specific symptom clusters. It is worth noting that the widespread application of immunotherapy has increased the complexity of the symptom burden and related symptom clusters in lung cancer. This has led to a growing need for scientific and comprehensive symptom management in clinical practice. Therefore, we included an irAE symptom item scale in the present study to address this gap. Unlike certain studies that have merely focused on single time points and neglected the dynamic trajectories of symptoms [27], our study involved the collection of PRO data from patients with advanced lung cancer over six cycles of immunotherapy‐based combination treatment. Scale data were collected at five points during each cycle: before treatment, on the day of treatment, 1 week after treatment, 2 weeks after treatment, and 3 weeks after treatment. Therefore, the collected data was able to provide a better reflection of short‐term symptom changes and facilitate comprehensive dynamic recording and analysis.
A total of 168 patients with advanced primary lung cancer from multiple study centres were included in this study, based on the inclusion and exclusion criteria. Our results revealed differences in the distribution of patient‐reported symptoms before and after first‐line immunotherapy‐based combination treatment. The most common patient‐reported symptoms before treatment were coughing, shortness of breath, distress, sadness, and disturbed sleep, whereas symptoms commonly reported after treatment were coughing, fatigue, lack of appetite, shortness of breath, and disturbed sleep. These findings somewhat differ from the symptom experiences of patients with NSCLC reported by Whisenant et al., which indicated that shortness of breath, coughing, distress, fatigue, pain, and constipation were commonly reported. In patients who received chemotherapy, neuropathy and a sore mouth were the most commonly reported treatment‐related symptoms [28]. We analyzed the longitudinal trends and characteristics of changes of the top five symptoms with the highest baseline mean scores. Coughing was the main symptom throughout the entire course of treatment. Its incidence, severity, and the proportion of reports of moderate‐to‐severe symptoms decreased after treatment, with the symptom trajectory showing a continuously decreasing trend. Shortness of breath was also a common lung cancer‐related symptom and exhibited a general trend of alleviation. Although its peak value did not exhibit a linear relationship with time, the trough value gradually decreased with ongoing treatment. In addition, the proportion of patients reporting moderate‐to‐severe symptoms decreased from 22.62% before treatment to 10.71% after treatment. This indicated that shortness of breath was significantly alleviated after combination treatment with chemotherapy and immunotherapy. The mean scores of distress, disturbed sleep, and pain decreased to levels below the baseline after treatment. The linear mixed‐effects models suggested an overall decreasing trend. However, further analysis of the cyclical variation characteristics revealed that the peak and trough values of the symptoms mentioned above did not decrease with an increased number of treatment cycles. This may be attributed to the relatively small proportion of patients with baseline moderate‐to‐severe symptoms, wherein relief effects were likely diluted by the cohort with minimal baseline symptomatology. Another study reported that fatigue was the most severe symptom throughout the course of chemoradiotherapy in a cohort of patients with NSCLC [29]. This is similar to our findings in an observational cohort of patients receiving immunotherapy. Fatigue was the most frequently reported and highest‐scoring toxic side effect after treatment. Its score often reached the peak value on the day of treatment or 1 week after treatment and gradually decreased thereafter, with this trend repeating with each cycle. This may be attributed to the increased physical burden and decreased quality of life caused by common post‐chemotherapy symptoms, such as vomiting and lack of appetite [30].
All the patients in the present study underwent first‐line immunotherapy‐based combination treatment. Observations of the patients' immunotherapy drug‐related symptoms revealed an increase in the occurrence rates and severity of symptoms such as rash, pruritus, abdominal distension, early satiety, bloated pain, and altered sense of taste. This may be related to skin, gastrointestinal, and nervous system toxicities caused by ICIs. Treatment with ICIs may also lead to systemic reactions, such as fever, fatigue, and muscle pain [31, 32, 33, 34]. Immune‐related adverse reactions observed in the present study mainly manifested in the gastrointestinal tract and nervous system. They included early satiety, abdominal distension, night sweat, altered sense of taste, with bloated pain being the most common symptom. The symptoms reached peak severity on the day of treatment or 1 week after treatment and showed gradual attenuation afterward. However, they exhibited a cyclical steady increase in severity with ongoing treatment. These findings indicate that immunotherapy‐related adverse effects persist throughout treatment and may exhibit cumulative patterns, underscoring the critical need for implementing a proactive monitoring system spanning the entire therapeutic course. Additionally, clinicians should intensify surveillance during high‐risk periods (e.g., targeted laboratory assessments at specific timepoints) and initiate prompt intervention while adverse reactions remain low‐grade to prevent progression to higher severity levels.
Subgroup analyses revealed heightened symptom burden in stage IV patients for both lung cancer‐related and immunotherapy‐related symptoms, underscoring the necessity of prioritized symptom management and early intervention for immune‐mediated toxicities in the stage IV population. The phase III IMpower150 trial established a ICIs + chemotherapy + VEGFR‐TKIs regimen as first‐line treatment for advanced NSCLC [35]. Our study included 34 patients receiving this regimen. Results demonstrated significantly lower lung cancer‐related symptom burden compared to a conventional ICIs + chemotherapy regimen, without increased toxicity—consistent with IMpower150's safety‐efficacy profile. We will further validate these findings through a prospective comparative study of symptom trajectories between these two therapeutic approaches in advanced NSCLC.
The present ePRO‐based prospective, multicentre clinical study had some limitations: (1) the adoption of patients' self‐reports of symptoms for data collection posed a certain demand on the level of patient comprehension and cognitive feedback. This resulted in a relatively small sample size despite the participation of multiple tumor centres; (2) the MDASI‐LC is an internationally recognized lung cancer‐specific scale, and its Chinese version has been developed and validated [36]. However, the scale consists of a considerable number of follow‐up items. With the variation of the comprehensive ability across patients of different educational backgrounds and the large number of follow‐ups, there may be non‐uniformities in symptom description and assessment among the patients, despite the instructions and guidance on scale completion by the researchers throughout the entire study period.
5. Conclusions
This study's results indicate that patients who received first‐line immunotherapy‐based combination treatment experienced a decrease in the severity of lung cancer‐specific symptoms and an increase in the severity of treatment‐related and immune‐specific symptoms. The addition of anti‐angiogenic therapy to ICIs + chemotherapy did not increase the associated toxicity burden.
Author Contributions
Conception and design: Jin Zhou, Rong Jia, and Junyi Zou. Provision of study materials or patients: Xiaoshan Wang, Yuzhu Zheng, Yi Wang, Jianning Tang, Lingna Kou, Yang Liu, Jing Ding, and Xin Li. Collection of data: Han Hu, Fan Yang, Yan Pang, and Ke Wang. Data analysis: Rong Jia, Junyi Zou. Revision of manuscript: Wei Dai, Xing Wei, Qiuling Shi, Jin Zhou. Manuscript writing: All authors. Final approval of manuscript: All authors.
Ethics Statement
This prospective, multicentre, observational study was approved by the ethics committee of Sichuan Cancer Hospital (approval number: SCCHEC‐02‐2022‐068), and the study was registered in the Chinese Clinical Trial Registry (registration number: ChiCTR2200061540).
Consent
Informed consent to participate in this study was obtained from all participants. Our research adheres to the Declaration of Helsinki.
Conflicts of Interest
The authors declare no conflicts of interest.
Supporting information
Data S1: tca70155‐sup‐0001‐Supplemental_Material.pdf.
Acknowledgments
The authors have nothing to report.
Jia R., Zou J., Hu H., et al., “Patient‐Reported Outcomes With First‐Line Immunotherapy‐Based Combination Treatment for Advanced Lung Cancer: A Prospective, Multicenter, Observational Study,” Thoracic Cancer 16, no. 18 (2025): e70155, 10.1111/1759-7714.70155.
Funding: This work was supported by Guangdong Association of Clinical Trials (GACT)/Chinese Thoracic Oncology Group (CTONG) and Guangdong Provincial Key Lab of Translational Medicine in Lung Cancer (Grant No. YC20210105), 2022CSCO key program (Y‐2021AST/zd‐0119), and Construction of the whole process management and rehabilitation evaluation system of immunotherapy for advanced lung cancer based on patient‐reported outcomes (PRO) (2025YFHZ0248).
Rong Jia, Junyi Zou contributed equally to this work.
Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.
References
- 1. Siegel R. L., Miller K. D., Wagle N. S., and Jemal A., “Cancer Statistics, 2023,” CA: A Cancer Journal for Clinicians 73, no. 1 (2023): 17–48. [DOI] [PubMed] [Google Scholar]
- 2. Chansky K., Detterbeck F. C., Nicholson A. G., et al., “The IASLC Lung Cancer Staging Project: External Validation of the Revision of the TNM Stage Groupings in the Eighth Edition of the TNM Classification of Lung Cancer,” Journal of Thoracic Oncology 12, no. 7 (2017): 1109–1121. [DOI] [PubMed] [Google Scholar]
- 3. Herbst R. S., Morgensztern D., and Boshoff C., “The Biology and Management of Non‐Small Cell Lung Cancer,” Nature 553, no. 7689 (2018): 446–454. [DOI] [PubMed] [Google Scholar]
- 4. Reck M., Remon J., and Hellmann M. D., “First‐Line Immunotherapy for Non‐Small‐Cell Lung Cancer,” Journal of Clinical Oncology 40, no. 6 (2022): 586–597. [DOI] [PubMed] [Google Scholar]
- 5. Garon E. B., Hellmann M. D., Rizvi N. A., et al., “Five‐Year Overall Survival for Patients With Advanced Non–Small‐Cell Lung Cancer Treated With Pembrolizumab: Results From the Phase I KEYNOTE‐001 Study,” Journal of Clinical Oncology 37, no. 28 (2019): 2518–2527. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6. Borghaei H., Gettinger S., Vokes E. E., et al., “Five‐Year Outcomes From the Randomized, Phase III Trials CheckMate 017 and 057: Nivolumab Versus Docetaxel in Previously Treated Non‐Small‐Cell Lung Cancer,” Journal of Clinical Oncology 39, no. 7 (2021): 723–733. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7. Bhatt A. S., Schabath M. B., Hoogland A. I., Jim H. S. L., and Brady‐Nicholls R., “Patient‐Reported Outcomes as Interradiographic Predictors of Response in Non‐Small Cell Lung Cancer,” Clinical Cancer Research 29, no. 16 (2023): 3142–3150. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8. Catto J. W. F., Downing A., Mason S., et al., “Quality of Life After Bladder Cancer: A Cross‐Sectional Survey of Patient‐Reported Outcomes,” European Urology 79, no. 5 (2021): 621–632. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9. Dai W., Feng W., Zhang Y., et al., “Patient‐Reported Outcome‐Based Symptom Management Versus Usual Care After Lung Cancer Surgery: A Multicenter Randomized Controlled Trial,” Journal of Clinical Oncology 40, no. 9 (2022): 988–996. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10. Guidance for Industry: Patient‐Reported Outcome Measures: Use in Medical Product Development to Support Labeling Claims: Draft Guidance,” Health and Quality of Life Outcomes 4 (2006): 79. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11. Paparrizos J., White R. W., and Horvitz E., “Screening for Pancreatic Adenocarcinoma Using Signals From Web Search Logs: Feasibility Study and Results,” Journal of Oncology Practice 12, no. 8 (2016): 737–744. [DOI] [PubMed] [Google Scholar]
- 12. White R. W. and Horvitz E., “Evaluation of the Feasibility of Screening Patients for Early Signs of Lung Carcinoma in Web Search Logs,” JAMA Oncology 3, no. 3 (2017): 398–401. [DOI] [PubMed] [Google Scholar]
- 13. Barata A., Hoogland A. I., Kommalapati A., et al., “Change in Patients' Perceived Cognition Following Chimeric Antigen Receptor T‐Cell Therapy for Lymphoma,” Transplantation and Cellular Therapy 28, no. 7 (2022): 401.e1–401.e7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14. Kerrigan K., Patel S. B., Haaland B., et al., “Prognostic Significance of Patient‐Reported Outcomes in Cancer,” JCO Oncology Practice 16, no. 4 (2020): e313–e323. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15. Efficace F., Collins G. S., Cottone F., et al., “Patient‐Reported Outcomes as Independent Prognostic Factors for Survival in Oncology: Systematic Review and Meta‐Analysis,” Value in Health 24, no. 2 (2021): 250–267. [DOI] [PubMed] [Google Scholar]
- 16. Turner K., Brownstein N. C., Thompson Z., et al., “Longitudinal Patient‐Reported Outcomes and Survival Among Early‐Stage Non‐Small Cell Lung Cancer Patients Receiving Stereotactic Body Radiotherapy,” Radiotherapy and Oncology 167 (2022): 116–121. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17. Deng Y., Hu H., Jia R., et al., “Patient‐Reported Outcome (PRO)‐Based Symptom Assessment in Patients With Advanced Lung Cancer Receiving First‐Line Combination Immunotherapy: A Protocol for a Multicenter, Prospective, Observational Study,” BMC Pulmonary Medicine 23, no. 1 (2023): 176. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18. Mendoza T. R., Wang X. S., Lu C., et al., “Measuring the Symptom Burden of Lung Cancer: The Validity and Utility of the Lung Cancer Module of the M. D. Anderson Symptom Inventory,” Oncologist 16, no. 2 (2011): 217–227. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19. Bower J. E., Bak K., Berger A., et al., “Screening, Assessment, and Management of Fatigue in Adult Survivors of Cancer: An American Society of Clinical Oncology Clinical Practice Guideline Adaptation,” Journal of Clinical Oncology 32, no. 17 (2014): 1840–1850. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20. Swarm R. A., Paice J. A., Anghelescu D. L., et al., “Adult Cancer Pain, Version 3.2019, NCCN Clinical Practice Guidelines in Oncology,” Journal of the National Comprehensive Cancer Network 17, no. 8 (2019): 977–1007. [DOI] [PubMed] [Google Scholar]
- 21. Freites‐Martinez A., Santana N., Arias‐Santiago S., et al., “Using the Common Terminology Criteria for Adverse Events (CTCAE ‐ Version 5.0) to Evaluate the Severity of Adverse Events of Anticancer Therapies,” Actas Dermo‐Sifiliográficas 112, no. 1 (2021): 90–92. [DOI] [PubMed] [Google Scholar]
- 22. Harvey L. A., “REDCap: Web‐Based Software for All Types of Data Storage and Collection,” Spinal Cord 56, no. 7 (2018): 625. [DOI] [PubMed] [Google Scholar]
- 23. Eisenhauer E. A., Therasse P., Bogaerts J., et al., “New Response Evaluation Criteria in Solid Tumours: Revised RECIST Guideline (Version 1.1),” European Journal of Cancer 45, no. 2 (2009): 228–247. [DOI] [PubMed] [Google Scholar]
- 24. Brahmer J. R., RODRíGUEZ‐ABREU D., Robinson A. G., et al., “Health‐Related Quality‐Of‐Life Results for Pembrolizumab Versus Chemotherapy in Advanced, PD‐L1‐Positive NSCLC (KEYNOTE‐024): A Multicentre, International, Randomised, Open‐Label Phase 3 Trial,” Lancet Oncology 18, no. 12 (2017): 1600–1609. [DOI] [PubMed] [Google Scholar]
- 25. Garassino M. C., Gadgeel S., Esteban E., et al., “Patient‐Reported Outcomes Following Pembrolizumab or Placebo Plus Pemetrexed and Platinum in Patients With Previously Untreated, Metastatic, Non‐Squamous Non‐Small‐Cell Lung Cancer (KEYNOTE‐189): A Multicentre, Double‐Blind, Randomised, Placebo‐Controlled, Phase 3 Trial,” Lancet Oncology 21, no. 3 (2020): 387–397. [DOI] [PubMed] [Google Scholar]
- 26. Reck M., Schenker M., Lee K. H., et al., “Nivolumab Plus Ipilimumab Versus Chemotherapy as First‐Line Treatment in Advanced Non‐Small‐Cell Lung Cancer With High Tumour Mutational Burden: Patient‐Reported Outcomes Results From the Randomised, Open‐Label, Phase III CheckMate 227 Trial,” European Journal of Cancer 116 (2019): 137–147. [DOI] [PubMed] [Google Scholar]
- 27. Zhang G., Weng H., Li Y., et al., “Symptom Clusters and Their Predictors in Patients With Lung Cancer and Treated With Programmed Cell Death Protein 1 Immunotherapy,” Asia‐Pacific Journal of Oncology Nursing 9, no. 8 (2022): 100103. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28. Whisenant M. S., Williams L. A., Garcia Gonzalez A., et al., “What Do Patients With Non‐Small‐Cell Lung Cancer Experience? Content Domain for the MD Anderson Symptom Inventory for Lung Cancer,” JCO Oncology Practice 16, no. 10 (2020): e1151–e1160. [DOI] [PubMed] [Google Scholar]
- 29. Wang X. S., Fairclough D. L., Liao Z., et al., “Longitudinal Study of the Relationship Between Chemoradiation Therapy for Non‐Small‐Cell Lung Cancer and Patient Symptoms,” Journal of Clinical Oncology 24, no. 27 (2006): 4485–4491. [DOI] [PubMed] [Google Scholar]
- 30. Poon K. S., Un M. K., Low X. H., et al., “Impact of Cancer‐Related Fatigue on Chemotherapy‐Induced Nausea and Vomiting in Asian Cancer Patients,” Pharmacoepidemiology and Drug Safety 22, no. 12 (2013): 1345–1351. [DOI] [PubMed] [Google Scholar]
- 31. Darnell E. P., Mooradian M. J., Baruch E. N., Yilmaz M., and Reynolds K. L., “Immune‐Related Adverse Events (irAEs): Diagnosis, Management, and Clinical Pearls,” Current Oncology Reports 22, no. 4 (2020): 39. [DOI] [PubMed] [Google Scholar]
- 32. Geisler A. N., Phillips G. S., Barrios D. M., et al., “Immune Checkpoint Inhibitor‐Related Dermatologic Adverse Events,” Journal of the American Academy of Dermatology 83, no. 5 (2020): 1255–1268. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33. Morimoto K., Yamada T., Takumi C., et al., “Immune‐Related Adverse Events Are Associated With Clinical Benefit in Patients With Non‐Small‐Cell Lung Cancer Treated With Immunotherapy Plus Chemotherapy: A Retrospective Study,” Frontiers in Oncology 11 (2021): 630136. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34. Shankar B., Zhang J., Naqash A. R., et al., “Multisystem Immune‐Related Adverse Events Associated With Immune Checkpoint Inhibitors for Treatment of Non‐Small Cell Lung Cancer,” JAMA Oncology 6, no. 12 (2020): 1952–1956. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35. Reck M., Wehler T., Orlandi F., et al., “Safety and Patient‐Reported Outcomes of Atezolizumab Plus Chemotherapy With or Without Bevacizumab Versus Bevacizumab Plus Chemotherapy in Non‐Small‐Cell Lung Cancer,” Journal of Clinical Oncology 38, no. 22 (2020): 2530–2542. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36. Silvoniemi M., Vasankari T., Löyttyniemi E., et al., “Symptom Assessment for Patients With Non‐Small Cell Lung Cancer Scheduled for Chemotherapy,” Anticancer Research 36, no. 8 (2016): 4123–4128. [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data S1: tca70155‐sup‐0001‐Supplemental_Material.pdf.
Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.