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Fujimoto D, Hayashi H, Murotani K, Toi Y, Yokoyama T, Kato T, Yamaguchi T, Tanaka K, Miura S, Tamiya M, Tachihara M, Shukuya T, Tsuchiya-Kawano Y, Sato Y, Ikeda S, Sakata S, Masuda T, Takemoto S, Otsubo K, Shibaki R, Makino M, Okamoto I, Yamamoto N. Prediction of prognosis in lung cancer using machine learning with inter-institutional generalizability: A multicenter cohort study (WJOG15121L: REAL-WIND). Lung Cancer 2024; 194:107896. [PMID: 39043076 DOI: 10.1016/j.lungcan.2024.107896] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2024] [Revised: 05/19/2024] [Accepted: 07/14/2024] [Indexed: 07/25/2024]
Abstract
OBJECTIVES Predicting the prognosis of lung cancer is crucial for providing optimal medical care. However, a method to accurately predict the overall prognosis in patients with stage IV lung cancer, even with the use of machine learning, has not been established. Moreover, the inter-institutional generalizability of such algorithms remains unexplored. This study aimed to establish machine learning-based algorithms with inter-institutional generalizability to predict prognosis. MATERIALS AND METHODS This multicenter, retrospective, hospital-based cohort study included consecutive patients with stage IV lung cancer who were randomly categorized into the training and independent test cohorts with a 2:1 ratio, respectively. The primary metric to assess algorithm performance was the area under the receiver operating characteristic curve in the independent test cohort. To assess the inter-institutional generalizability of the algorithms, we investigated their ability to predict patient outcomes in the remaining facility after being trained using data from 15 other facilities. RESULTS Overall, 6,751 patients (median age, 70 years) were enrolled, and 1,515 (22 %) showed mutated epidermal growth factor receptor expression. The median overall survival was 16.6 (95 % confidence interval, 15.9-17.5) months. Algorithm performance metrics in the test cohort showed that the areas under the curves were 0.90 (95 % confidence interval, 0.88-0.91), 0.85 (0.84-0.87), 0.83 (0.81-0.85), and 0.85 (0.82-0.87) at 180, 360, 720, and 1,080 predicted survival days, respectively. The performance test of 16 algorithms for investigating inter-institutional generalizability showed median areas under the curves of 0.87 (range, 0.84-0.92), 0.84 (0.78-0.88), 0.84 (0.76-0.89), and 0.84 (0.75-0.90) at 180, 360, 720, and 1,080 days, respectively. CONCLUSION This study developed machine learning algorithms that could accurately predict the prognosis in patients with stage IV lung cancer with high inter-institutional generalizability. This can enhance the accuracy of prognosis prediction and support informed and shared decision-making in clinical settings.
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Affiliation(s)
- Daichi Fujimoto
- Internal Medicine III, Wakayama Medical University, Wakayama, Japan
| | - Hidetoshi Hayashi
- Department of Medical Oncology, Kindai University Faculty of Medicine, Osaka, Japan.
| | | | - Yukihiro Toi
- Department of Pulmonary Medicine, Sendai Kousei Hospital, Sendai, Japan
| | - Toshihide Yokoyama
- Department of Respiratory Medicine, Kurashiki Central Hospital, Kurashiki, Japan
| | - Terufumi Kato
- Department of Thoracic Oncology, Kanagawa Cancer Center, Yokohama, Japan
| | - Teppei Yamaguchi
- Department of Thoracic Oncology, Aichi Cancer Center Hospital, Nagoya, Japan
| | - Kaoru Tanaka
- Department of Medical Oncology, Kindai University Faculty of Medicine, Osaka, Japan
| | - Satoru Miura
- Department of Internal Medicine, Niigata Cancer Center Hospital, Niigata, Japan
| | - Motohiro Tamiya
- Department of Thoracic Oncology, Osaka International Cancer Institute, Osaka, Japan
| | - Motoko Tachihara
- Division of Respiratory Medicine, Department of Internal Medicine, Kobe University Graduate School of Medicine, Kobe, Japan
| | - Takehito Shukuya
- Department of Respiratory Medicine, Juntendo University, Graduate School of Medicine, Tokyo, Japan
| | - Yuko Tsuchiya-Kawano
- Department of Respiratory Medicine, Kitakyushu Municipal Medical Center, Kitakyushu, Japan
| | - Yuki Sato
- Department of Respiratory Medicine, Kobe City Medical Center General Hospital, Kobe, Japan
| | - Satoshi Ikeda
- Department of Respiratory Medicine, Kanagawa Cardiovascular and Respiratory Center, Yokohama, Japan
| | - Shinya Sakata
- Department of Respiratory Medicine, Kumamoto University Hospital, Kumamoto, Japan
| | - Takeshi Masuda
- Department of Respiratory Medicine, Hiroshima University Hospital, Hiroshima, Japan
| | - Shinnosuke Takemoto
- Department of Respiratory Medicine, Nagasaki University Graduate School of Biomedical Sciences, Nagasaki, Japan
| | - Kohei Otsubo
- Department of Respiratory Medicine, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Ryota Shibaki
- Internal Medicine III, Wakayama Medical University, Wakayama, Japan
| | - Miki Makino
- NTT Data Corp., Res. & Dev. Headquarters, Tokyo, Japan
| | - Isamu Okamoto
- Department of Respiratory Medicine, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
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Misawa K, Watanabe K, Seike M, Hosomi Y. Durvalumab plus platinum-etoposide chemotherapy for extensive-stage small cell lung cancer: a retrospective real-world study. Transl Lung Cancer Res 2024; 13:1585-1594. [PMID: 39118881 PMCID: PMC11304155 DOI: 10.21037/tlcr-24-128] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2024] [Accepted: 05/27/2024] [Indexed: 08/10/2024]
Abstract
Background Immune checkpoint inhibitor plus platinum-etoposide (PE) improved overall survival (OS) in patients with extensive-stage small cell lung cancer (ES-SCLC). While the CASPIAN trial demonstrated the efficacy of durvalumab plus PE, the clinical trial results may not be representative of the general, real-world population because clinical trials often have strict inclusion and exclusion criteria. We herein report the efficacy and safety of durvalumab plus PE in patients with ES-SCLC in real-world, clinical practice. Methods The present, monocentric, retrospective study evaluated patients with ES-SCLC or recurrent, limited-stage SCLC who received durvalumab plus PE between September 2020 and February 2023. The efficacy and incidence of adverse events (AEs) were also evaluated. Results The study included 40 patients, of whom 17 were elderly (age >70 years), and 15 had performance status (PS) 2 or 3. The median follow-up time was 13.0 months [95% confidence interval (CI): 8.0-22.2 months]. The objective response rate was 80.0% (95% CI: 63.1-91.6%), and the disease control rate was 88.6% (95% CI: 73.3-96.8%). The median progression-free survival (PFS) was 5.9 months (95% CI: 4.9-6.9), and the median OS was 25.4 months (95% CI: 4.6-46.2). Factors such as advanced age, poor PS, and presence of brain metastases were not associated with lower PFS and OS. Twenty-six patients (65.0%) experienced grade 3 or higher AEs, mainly hematological toxicity. AEs leading to treatment discontinuation occurred in three patients (8%). Conclusions Durvalumab plus PE in patients with ES-SCLC showed good efficacy and safety according to our real-world data, suggesting that this treatment is well tolerated in clinical practice, even in elderly patients and those with poor PS.
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Affiliation(s)
- Kazuhito Misawa
- Department of Thoracic Oncology and Respiratory Medicine, Tokyo Metropolitan Cancer and Infectious Diseases Center, Komagome Hospital, Tokyo, Japan
- Department of Pulmonary Medicine and Oncology, Graduate School of Medicine, Nippon Medical School, Tokyo, Japan
| | - Kageaki Watanabe
- Department of Thoracic Oncology and Respiratory Medicine, Tokyo Metropolitan Cancer and Infectious Diseases Center, Komagome Hospital, Tokyo, Japan
| | - Masahiro Seike
- Department of Pulmonary Medicine and Oncology, Graduate School of Medicine, Nippon Medical School, Tokyo, Japan
| | - Yukio Hosomi
- Department of Thoracic Oncology and Respiratory Medicine, Tokyo Metropolitan Cancer and Infectious Diseases Center, Komagome Hospital, Tokyo, Japan
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Nishimura T, Fujimoto H, Fujiwara T, Ito K, Fujiwara A, Yuda H, Itani H, Naito M, Kodama S, Furuhashi K, Yagi A, Saiki H, Yasuma T, Okano T, Tomaru A, Tanigawa M, Yoshida M, Hataji O, Ibata H, D'Alessandro‐Gabazza CN, Gabazza EC, Kobayashi T. Impact of immune-related adverse events on survival outcomes in extensive-stage small cell lung cancer patients treated with immune checkpoint inhibitors. Cancer Med 2024; 13:e7188. [PMID: 38629295 PMCID: PMC11022147 DOI: 10.1002/cam4.7188] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Revised: 01/27/2024] [Accepted: 04/02/2024] [Indexed: 04/19/2024] Open
Abstract
BACKGROUND Immune checkpoint inhibitors have recently become the standard of care in the first-line treatment of extensive-stage small cell lung cancer. Although immune-related adverse events have been reported to influence prognosis in non-small cell lung cancer patients, few studies have investigated the prognostic value of immune-related adverse events in small cell lung cancer patients. In this study, we evaluated the prognosis of patients who developed immune-related adverse events after first-line treatment with immune checkpoint inhibitor-based chemotherapy for extensive-stage small cell lung cancer. METHODS We enrolled 90 patients with extensive-stage small cell lung cancer who received immune checkpoint inhibitor-based chemotherapy as first-line treatment from September 2019 to December 2022 in six hospitals in Japan. The patients were categorized into groups with and without immune-related adverse events. RESULTS There were 23 patients with and 67 without immune-related adverse events. Seventeen patients had grade 1-2 immune-related adverse events, and nine (including overlapping cases) had grade ≥3. The most frequent immune-related adverse event was a skin rash. The median survival time was 22 months in patients with immune-related adverse events and 9.3 months in patients without immune-related adverse events. The hazard ratio was 0.40 (95% confidence interval: 0.19-0.83, p = 0.013). CONCLUSIONS The results of this study show that immune-related adverse events are associated with improved survival outcomes in patients with extensive-stage small cell lung cancer.
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Affiliation(s)
- Tadashi Nishimura
- Department of Pulmonary MedicineMie Chuo Medical CenterTsuJapan
- Department of Pulmonary and Critical Care MedicineMie University Faculty and Graduate School of MedicineTsuJapan
| | - Hajime Fujimoto
- Department of Pulmonary and Critical Care MedicineMie University Faculty and Graduate School of MedicineTsuJapan
| | - Takumi Fujiwara
- Department of Pulmonary and Critical Care MedicineMie University Faculty and Graduate School of MedicineTsuJapan
- Department of Genomic MedicineMie University HospitalTsuJapan
| | - Kentaro Ito
- Respiratory CenterMatsusaka Municipal HospitalMatsusakaJapan
| | - Atsushi Fujiwara
- Department of Pulmonary MedicineMie Prefectural General Medical CenterYokkaichiJapan
| | - Hisamichi Yuda
- Department of Pulmonary MedicineKuwana City Medical CenterKuwanaJapan
| | - Hidetoshi Itani
- Department of Respiratory MedicineIse Red Cross HospitalIseJapan
| | - Masahiro Naito
- Department of Pulmonary MedicineMie Chuo Medical CenterTsuJapan
| | - Shuji Kodama
- Department of Pulmonary MedicineMie Prefectural General Medical CenterYokkaichiJapan
| | - Kazuki Furuhashi
- Department of Pulmonary and Critical Care MedicineMie University Faculty and Graduate School of MedicineTsuJapan
| | - Akihiko Yagi
- Department of Pulmonary and Critical Care MedicineMie University Faculty and Graduate School of MedicineTsuJapan
| | - Haruko Saiki
- Department of Pulmonary and Critical Care MedicineMie University Faculty and Graduate School of MedicineTsuJapan
| | - Taro Yasuma
- Department of ImmunologyMie University Faculty and Graduate School of MedicineTsuJapan
| | - Tomohito Okano
- Department of Pulmonary and Critical Care MedicineMie University Faculty and Graduate School of MedicineTsuJapan
| | - Atsushi Tomaru
- Department of Pulmonary and Critical Care MedicineMie University Faculty and Graduate School of MedicineTsuJapan
| | - Motoaki Tanigawa
- Department of Respiratory MedicineIse Red Cross HospitalIseJapan
| | - Masamichi Yoshida
- Department of Pulmonary MedicineMie Prefectural General Medical CenterYokkaichiJapan
| | - Osamu Hataji
- Respiratory CenterMatsusaka Municipal HospitalMatsusakaJapan
| | - Hidenori Ibata
- Department of Pulmonary MedicineMie Chuo Medical CenterTsuJapan
| | | | - Esteban C. Gabazza
- Department of Pulmonary and Critical Care MedicineMie University Faculty and Graduate School of MedicineTsuJapan
- Department of ImmunologyMie University Faculty and Graduate School of MedicineTsuJapan
| | - Tetsu Kobayashi
- Department of Pulmonary and Critical Care MedicineMie University Faculty and Graduate School of MedicineTsuJapan
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Porte M, Vaudron A, Crequit P, Vaugier L, Chatellier T, Fronteau C, Raimbourg J, Goronflot T, Bennouna J, Pons-Tostivint E. A Multicenter Study Assessing the Real-World Use and Effectiveness of First-Line Chemotherapy Plus Immunotherapy in Advanced Small-Cell Lung Cancer (SCLC) Patients. Clin Lung Cancer 2024; 25:e101-e111.e2. [PMID: 38072729 DOI: 10.1016/j.cllc.2023.11.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Revised: 10/31/2023] [Accepted: 11/16/2023] [Indexed: 03/01/2024]
Abstract
BACKGROUND First-line chemotherapy plus immunotherapy (CT-IO) has recently demonstrated survival benefits over CT alone in extensive-stage small-cell lung cancer (ES-SCLC), based on randomized phase III studies. This retrospective multicenter study assessed the real-world use and effectiveness of CT-IO in ES-SCLC patients. PATIENTS AND METHODS All newly diagnosed ES-SCLC patients from 4 French hospitals treated with CT alone or CT-IO between May 2020 and December 2021 were included. Overall survival (OS) and real-world progression-free survival (rwPFS) were estimated using the Kaplan-Meier method. Cox proportional hazard models were performed to estimate hazard ratios (HRs) with 95 % confidence intervals (CIs) in univariate and multivariate models. The aim was not to compare efficacy between groups. RESULTS Among 104 patients, 75 (72.1%) received CT-IO. Brain metastases were diagnosed in 28.3% of patients, and 29.8% were performance status (PS) ≥ 2. At a median follow-up of 16.8 months (95%CI, 14.9-23.4), the median OS was 11.4 months (95%CI, 7.7-14.7) in the CT-IO group, and the 12-month OS rate was 43.6% (95%CI, 33.3-57.2). In the CT group, the median OS was 7.8 months (95%CI, 5.4-11.8) and the 12-month OS rate was 15.3% (95%CI, 5.7-41.0). In multivariate analyses, baseline brain and liver metastases were associated with a shorter OS for patients treated in the CT-IO group (HR, 3.80 [95%CI, 1.90-7.60] and 3.12 [95%CI, 1.60-6.08] respectively; P < 0.001 for both). CONCLUSION We showed that clinicians have chosen to use IO beyond the specific criteria defined in guidelines. Survival data appeared promising with a median OS comparable to the one previously demonstrated in clinical trials.
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Affiliation(s)
- Marie Porte
- Department of Medical Oncology, Centre Hospitalier Universitaire Nantes, Nantes University, Nantes, France
| | - Adrien Vaudron
- Nantes Université, CHU Nantes, Pôle Hospitalo-Universitaire 11: Santé Publique, Clinique des données, INSERM, Nantes, France
| | - Perrine Crequit
- Department of Medical Oncology, Hospital Foch, Suresnes, France
| | - Loig Vaugier
- Department of Radiotherapy, Comprehensive Cancer Center, Institut de Cancérologie de l'Ouest, Saint-Herblain, France
| | - Thierry Chatellier
- Medical Oncology Unit, Clinique Mutualiste de l'Estuaire, Saint-Nazaire, France
| | | | - Judith Raimbourg
- Department of Medical Oncology, Comprehensive Cancer Center, Institut de Cancérologie de l'Ouest, Saint-Herblain, France; Nantes Université, Inserm UMR 1307, CNRS UMR 6075, Université d'Angers, CRCI2NA, Nantes, France
| | - Thomas Goronflot
- Nantes Université, CHU Nantes, Pôle Hospitalo-Universitaire 11: Santé Publique, Clinique des données, INSERM, Nantes, France
| | - Jaafar Bennouna
- Department of Medical Oncology, Hospital Foch, Suresnes, France
| | - Elvire Pons-Tostivint
- Department of Medical Oncology, Centre Hospitalier Universitaire Nantes, Nantes University, Nantes, France; Nantes Université, Inserm UMR 1307, CNRS UMR 6075, Université d'Angers, CRCI2NA, Nantes, France.
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Shibaki R, Fujimoto D, Nozawa T, Sano A, Kitamura Y, Fukuoka J, Sato Y, Kijima T, Matsumoto H, Yokoyama T, Miura S, Hata A, Tamiya M, Taniguchi Y, Sugisaka J, Furuya N, Tanaka H, Yamamoto N, Koh Y, Akamatsu H. Machine learning analysis of pathological images to predict 1-year progression-free survival of immunotherapy in patients with small-cell lung cancer. J Immunother Cancer 2024; 12:e007987. [PMID: 38360040 PMCID: PMC10875545 DOI: 10.1136/jitc-2023-007987] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/27/2024] [Indexed: 02/17/2024] Open
Abstract
BACKGROUND In small-cell lung cancer (SCLC), the tumor immune microenvironment (TIME) could be a promising biomarker for immunotherapy, but objectively evaluating TIME remains challenging. Hence, we aimed to develop a predictive biomarker of immunotherapy efficacy through a machine learning analysis of the TIME. METHODS We conducted a biomarker analysis in a prospective study of patients with extensive-stage SCLC who received chemoimmunotherapy as the first-line treatment. We trained a model to predict 1-year progression-free survival (PFS) using pathological images (H&E, programmed cell death-ligand 1 (PD-L1), and double immunohistochemical assay (cluster of differentiation 8 (CD8) and forkhead box P3 (FoxP3)) and patient information. The primary outcome was the mean area under the curve (AUC) of machine learning models in predicting the 1-year PFS. RESULTS We analyzed 100,544 patches of pathological images from 78 patients. The mean AUC values of patient information, pathological image, and combined models were 0.789 (range 0.571-0.982), 0.782 (range 0.750-0.911), and 0.868 (range 0.786-0.929), respectively. The PFS was longer in the high efficacy group than in the low efficacy group in all three models (patient information model, HR 0.468, 95% CI 0.287 to 0.762; pathological image model, HR 0.334, 95% CI 0.117 to 0.628; combined model, HR 0.353, 95% CI 0.195 to 0.637). The machine learning analysis of the TIME had better accuracy than the human count evaluations (AUC of human count, CD8-positive lymphocyte: 0.681, FoxP3-positive lymphocytes: 0.626, PD-L1 score: 0.567). CONCLUSIONS The spatial analysis of the TIME using machine learning predicted the immunotherapy efficacy in patients with SCLC, thus supporting its role as an immunotherapy biomarker.
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Affiliation(s)
- Ryota Shibaki
- Internal Medicine Ⅲ, Wakayama Medical University, Wakayama, Japan
| | - Daichi Fujimoto
- Internal Medicine Ⅲ, Wakayama Medical University, Wakayama, Japan
| | | | | | - Yuka Kitamura
- Department of pathology informatics, Nagasaki University Graduate School of Biomedical Sciences, Nagasaki, Japan
| | - Junya Fukuoka
- Department of pathology informatics, Nagasaki University Graduate School of Biomedical Sciences, Nagasaki, Japan
| | - Yuki Sato
- Department of Respiratory Medicine, Kobe City Medical Center General Hospital, Hyogo, Japan
| | - Takashi Kijima
- Department of Respiratory Medicine and Hematology, Hyogo Medical University, Hyogo, Japan
| | - Hirotaka Matsumoto
- Department of Respiratory Medicine, Hyogo Prefectural Amagasaki General Medical Center, Hyogo, Japan
| | - Toshihide Yokoyama
- Department of Respiratory Medicine, Kurashiki Central Hospital, Okayama, Japan
| | - Satoru Miura
- Department of Internal Medicine, Niigata Cancer Center Hospital, Niigata, Japan
| | - Akito Hata
- Division of Thoracic Oncology, Kobe Minimally Invasive Cancer Center, Hyogo, Japan
| | - Motohiro Tamiya
- Department of Thoracic Oncology, Osaka International Cancer Institute, Osaka, Japan
| | - Yoshihiko Taniguchi
- Department of Internal Medicine, NHO Kinki Chuo Chest Medical Center, Osaka, Japan
| | - Jun Sugisaka
- Department of Pulmonary Medicine, Sendai Kousei Hospital, Miyagi, Japan
| | - Naoki Furuya
- Division of Respiratory Medicine, Department of Internal Medicine, St. Marianna University School of Medicine, Kanagawa, Japan
| | - Hisashi Tanaka
- Department of Respiratory Medicine, Hirosaki University Graduate School of Medicine, Hirosaki, Aomori, Japan
| | - Nobuyuki Yamamoto
- Internal Medicine Ⅲ, Wakayama Medical University, Wakayama, Japan
- Center for Biomedical Sciences, Wakayama Medical University, Wakayama, Japan
| | - Yasuhiro Koh
- Internal Medicine Ⅲ, Wakayama Medical University, Wakayama, Japan
- Center for Biomedical Sciences, Wakayama Medical University, Wakayama, Japan
| | - Hiroaki Akamatsu
- Internal Medicine Ⅲ, Wakayama Medical University, Wakayama, Japan
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Zheng Y, Tan K, Wang A, Lu X, Dong H, Li J, Cui H. Treatment patterns and clinical outcomes in 157 patients with extensive-stage small cell lung cancer: real-world evidence from a single-center retrospective study. Front Oncol 2023; 13:1287628. [PMID: 38111524 PMCID: PMC10726005 DOI: 10.3389/fonc.2023.1287628] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2023] [Accepted: 11/20/2023] [Indexed: 12/20/2023] Open
Abstract
Background Immune checkpoint inhibitors (ICIs) have changed the therapeutic options for extensive-stage small-cell lung cancer (ES-SCLC). In this real-world study, we analyzed the treatment patterns in patients with ES-SCLC and evaluated the efficacy of chemotherapy combined with immunotherapy as first-line therapy. Methods A retrospective analysis was performed on patients with ES-SCLC who received treatment at China-Japan Friendship Hospital (Beijing, China) between August 1, 2020, and April 30, 2023. The treatment patterns appeared in the form of Sunburst Chart and Sankey diagram. The survival analyses were conducted by Kaplan-Meier curves. Results A total of 157 patients with ES-SCLC were retrospectively included. According to first-line therapy, patients were divided into the chemotherapy (CT) group (n=82) and chemo-immunotherapy (CIT) group (n=75). The median treatment lines were 2[1, 2] and cycles were 8[5, 12], respectively. 82 patients received the second line of therapy, followed by 37 for the third, 15 for the fourth, 11 for the fifth, and 5 for the sixth. Overall, the treatment patterns involved 11 options including 12 chemotherapy regimens, 11 ICIs, and 4 targeted agents. The second-line treatment pattern had the most options (9) and regimens (43). In the first 3 lines, chemotherapy was the largest proportion of treatment options. The addition of ICIs prolonged progression-free survival from 6.77 (95% confidence interval [CI], 6.00-7.87) to 7.33 (95% CI, 6.03-9.80) months (hazard ratio [HR]=0.67, 95% CI, 0.47-0.95; P=0.025), overall survival from 12.97 (10.90-23.3) to 14.33 (12.67-NA) months without statistically significant difference (HR=0.86, 95% CI, 0.55-1.34; P=0.505). Conclusion The treatment options of patients with ES-SCLC are more diversified. Combination therapy is the current trend, where chemotherapy is the cornerstone. Meanwhile, ICIs participate in almost all lines of treatment. However, the clinical efficacy remains barely satisfactory. We are urgently expecting more breakthrough therapies except immunology will be applied in the clinic.
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Affiliation(s)
- Yumin Zheng
- Graduate School, Beijing University of Chinese Medicine, Beijing, China
| | - Kexin Tan
- Graduate School, Beijing University of Chinese Medicine, Beijing, China
| | - Aolin Wang
- Graduate School, Beijing University of Chinese Medicine, Beijing, China
| | - Xingyu Lu
- Graduate School, Beijing University of Chinese Medicine, Beijing, China
| | - Huijing Dong
- Graduate School, Beijing University of Chinese Medicine, Beijing, China
| | - Jia Li
- Graduate School, Beijing University of Chinese Medicine, Beijing, China
| | - Huijuan Cui
- Department of Integrative Oncology, China-Japan Friendship Hospital, Beijing, China
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Mukherjee O, Rakshit S, Shanmugam G, Sarkar K. Role of chemotherapeutic drugs in immunomodulation of cancer. CURRENT RESEARCH IN IMMUNOLOGY 2023; 4:100068. [PMID: 37692091 PMCID: PMC10491645 DOI: 10.1016/j.crimmu.2023.100068] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Revised: 08/16/2023] [Accepted: 08/25/2023] [Indexed: 09/12/2023] Open
Abstract
The immune system has a variety of potential effects on a tumor microenvironment and the course of chemotherapy may vary according to that. Anticancer treatments can encourage the release of unwanted signals from senescent tumor cells or the removal of immune-suppressive cells, which can lead to immune system activation. Hence, by inducing an immunological response and conversely making cancer cells more vulnerable to immune attack, chemotherapeutic agents can destroy cancer cells. Furthermore, chemotherapy can activate anticancer immune effectors directly or indirectly by thwarting immunosuppressive pathways. Therefore, in this review, we discuss how chemotherapeutic agents take part in immunomodulation and the molecular mechanisms underlying them. We also focus on the importance of carefully addressing the conflicting effects of chemotherapy on immune responses when developing successful combination treatments based on chemotherapy and immune modulators.
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Affiliation(s)
- Oishi Mukherjee
- Department of Biotechnology, SRM Institute of Science and Technology, Kattankulathur, Chennai, Tamil Nadu, 603203, India
| | - Sudeshna Rakshit
- Department of Biotechnology, SRM Institute of Science and Technology, Kattankulathur, Chennai, Tamil Nadu, 603203, India
| | - Geetha Shanmugam
- Department of Biotechnology, SRM Institute of Science and Technology, Kattankulathur, Chennai, Tamil Nadu, 603203, India
| | - Koustav Sarkar
- Department of Biotechnology, SRM Institute of Science and Technology, Kattankulathur, Chennai, Tamil Nadu, 603203, India
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