A Combined Model Based on Bone Mineral Density for Noninvasive Prediction of Prognosis in Non-Small Cell Lung Cancer Patients Receiving Immune Checkpoint Inhibitors: A Multicenter Retrospective Study

Abstract

The prognostic value of baseline bone mineral density (BMD) and posttreatment BMD decrease (BMDD) in non-small cell lung cancer (NSCLC) patients receiving immune checkpoint inhibitor (ICI) treatment remains unclear. We assembled data of 2096 patients with advanced NSCLC from five institutions to develop a combined model incorporating BMD/BMDD and clinical characteristics for noninvasive prognosis prediction. BMD was automatically assessed using a deep learning-based method. Compared with the physiological BMD group and the non-severe BMDD group, the pathological BMD group and the severe BMDD group had shorter progression-free survival (PFS) (hazard ratio [HR]: 1.19, p = 0.003; and HR: 1.19, p = 0.002, respectively) and overall survival (OS) (HR: 1.31, p < 0.001; and HR: 1.30, p < 0.001). Compared with the single BMD/BMDD model, the combined model had higher Harrell's concordance indexes (c-indexes) (PFS: 0.580 and OS: 0.654). Transcriptomic analysis of 130 patients from the NSCLC radiogenomic cohort revealed upregulation of epithelial–mesenchymal transition, inflammatory, and hypoxia pathways, and increased macrophage infiltration in tumors of patients with pathological BMD. This study showed that lower baseline BMD and more severe BMDD are associated with poorer prognosis. BMD in combination with clinical characteristics can help to improve risk stratification and prognosis prediction.

Keywords

bone mineral density / bone mineral density decrease / immunotherapy / immune checkpoint inhibitors / non-small cell lung cancer / osteoporosis

References

[1] M. C. Garassino, S. Gadgeel, G. Speranza, et al., “Pembrolizumab Plus Pemetrexed and Platinum in Nonsquamous Non-Small-Cell Lung Cancer: 5-Year Outcomes From the Phase 3 KEYNOTE-189 Study,” Journal of Clinical Oncology 41, no. 11 (2023): 1992-1998.

[2] D. S. Ettinger, D. E. Wood, D. L. Aisner, et al., “Non-Small Cell Lung Cancer, Version 3.2022, NCCN Clinical Practice Guidelines in Oncology,” Journal of the National Comprehensive Cancer Network 20, no. 5 (2022): 497-530.

[3] M. V. Negrao, F. Skoulidis, M. Montesion, et al., “Oncogene-Specific Differences in Tumor Mutational Burden, PD-L1 Expression, and Outcomes From Immunotherapy in Non-Small Cell Lung Cancer,” Journal for ImmunoTherapy of Cancer 9, no. 8 (2021): e002891.

[4] M. D. Hellmann, T. E. Ciuleanu, A. Pluzanski, et al., “Nivolumab Plus Ipilimumab in Lung Cancer With a High Tumor Mutational Burden,” New England Journal of Medicine 378, no. 22 (2018): 2093-2104.

[5] X. Shi, X. Cheng, A. Jiang, et al., “Immune Checkpoints in B Cells: Unlocking New Potentials in Cancer Treatment,” Advanced Science 11, no. 47 (2024): e2403423.

[6] A. Lin, A. Jiang, L. Huang, et al., “From Chaos to Order: Optimizing Fecal Microbiota Transplantation for Enhanced Immune Checkpoint Inhibitors Efficacy,” Gut Microbes 17, no. 1 (2025): 2452277.

[7] L. Liu, Y. Xie, H. Yang, et al., “HPVTIMER: A Shiny Web Application for Tumor Immune Estimation in Human Papillomavirus-Associated Cancers,” iMeta 2, no. 3 (2023): e130.

[8] G. Malietzis, N. Johns, H. O. Al-Hassi, et al., “Low Muscularity and Myosteatosis Is Related to the Host Systemic Inflammatory Response in Patients Undergoing Surgery for Colorectal Cancer,” Annals of Surgery 263, no. 2 (2016): 320-325.

[9] J. E. Park, J. Jo, and J. Youk, “Prognostic Utility of Body Composition Parameters Based on Computed Tomography Analysis of Advanced Non-Small Cell Lung Cancer Treated With Immune Checkpoint Inhibitors,” Insights Imaging 14, no. 1 (2023): 182.

[10] I. Trestini, L. Belluomini, A. Dodi, et al., “Body Composition Derangements in Lung Cancer Patients Treated With First-Line Pembrolizumab: A Multicentre Observational Study,” Journal of Cachexia, Sarcopenia and Muscle 15, no. 6 (2024): 2349-2360.

[11] J. F. Huang, Q. C. Tan, H. Bai, J. Wang, M. Bergman, and Z. Wu, “Bone Mineral Density, Osteopenia and Osteoporosis Among US Adults With Cancer,” QJM 115, no. 10 (2022): 653-660.

[12] J. A. Kanis, “Diagnosis of Osteoporosis and Assessment of Fracture Risk,” Lancet 359, no. 9321 (2002): 1929-1936.

[13] S. Jang, P. M. Graffy, T. J. Ziemlewicz, S. J. Lee, R. M. Summers, and P. J. Pickhardt, “Opportunistic Osteoporosis Screening at Routine Abdominal and Thoracic CT: Normative L1 Trabecular Attenuation Values in More Than 20 000 Adults,” Radiology 291, no. 2 (2019): 360-367.

[14] M. S. Jordens, L. Wittig, C. Loberg, et al., “Bone Mineral Density Is a Predictor of Mortality in Female Patients With Cholangiocellular Carcinoma Undergoing Palliative Treatment,” Biomedicines 10, no. 7 (2022): 1660.

[15] I. Ilic, A.-L. Potthoff, V. Borger, et al., “Bone Mineral Density as an Individual Prognostic Biomarker in Patients With Surgically-Treated Brain Metastasis From Lung Cancer (NSCLC),” Cancers 14, no. 19 (2022): 4633.

[16] C. Guder, S. Gravius, C. Burger, D. C. Wirtz, and F. A. Schildberg, “Osteoimmunology: A Current Update of the Interplay between Bone and the Immune System,” Frontiers in Immunology 11 (2020): 58.

[17] P. A. van Dam, Y. Verhoeven, X. B. Trinh, et al., “RANK/RANKL Signaling Inhibition May Improve the Effectiveness of Checkpoint Blockade in Cancer Treatment,” Critical Reviews in Oncology/Hematology 133 (2019): 85-91.

[18] D. H. Jones, T. Nakashima, O. H. Sanchez, et al., “Regulation of Cancer Cell Migration and Bone Metastasis by RANKL,” Nature 440, no. 7084 (2006): 692-696.

[19] R. Lorente-Ramos, J. Azpeitia-Armán, A. Muñoz-Hernández, J. M. García-Gómez, P. Díez-Martínez, and M. Grande-Bárez, “Dual-Energy X-Ray Absorptiometry in the Diagnosis of Osteoporosis: A Practical Guide,” AJR American Journal of Roentgenology 196, no. 4 (2011): 897-904.

[20] N. Deshpande, M. S. Hadi, J. C. Lillard, et al., “Alternatives to DEXA for the Assessment of Bone Density: A Systematic Review of the Literature and Future Recommendations,” Journal of Neurosurgery Spine 38, no. 4 (2023): 436-445.

[21] J. Watanabe, A. Saitsu, A. Miki, K. Kotani, and N. Sata, “Prognostic Value of Preoperative Low Bone Mineral Density in Patients With Digestive Cancers: A Systematic Review and Meta-Analysis,” Arch Osteoporos 17, no. 1 (2022): 33.

[22] L. Müller, A. Mähringer-Kunz, T. A. Auer, et al., “Low Bone Mineral Density Is a Prognostic Factor for Elderly Patients With HCC Undergoing TACE: Results From a Multicenter Study,” European Radiology 33, no. 2 (2023): 1031-1039.

[23] J. Lou, B. Gong, Y. Li, et al., “Bone Mineral Density as an Individual Prognostic Biomarker in NSCLC Patients Treated With Immune Checkpoint Inhibitors,” Frontiers in Immunology 15 (2024): 1332303.

[24] K. Polzer, L. Joosten, J. Gasser, et al., “Interleukin-1 Is Essential for Systemic Inflammatory Bone Loss,” Annals of the Rheumatic Diseases 69, no. 1 (2010): 284-290.

[25] O. Kudo, A. Sabokbar, A. Pocock, I. Itonaga, Y. Fujikawa, and N. A. Athanasou, “Interleukin-6 and Interleukin-11 Support Human Osteoclast Formation by a RANKL-Independent Mechanism,” Bone 32, no. 1 (2003): 1-7.

[26] S. A. Samant, A. Kanwal, V. B. Pillai, R. Bao, and M. P. Gupta, “The Histone Deacetylase SIRT6 Blocks Myostatin Expression and Development of Muscle Atrophy,” Scientific Reports 7, no. 1 (2017): 11877.

[27] M. Elsayed and C. Ye, “Osteoporotic Fractures: An Unrecognized Adverse Event of Immune Checkpoint Inhibitors?,” Journal for ImmunoTherapy of Cancer 12, no. 7 (2024): e009309.

[28] K. F. Moseley, J. Naidoo, C. O. Bingham, et al., “Immune-Related Adverse Events With Immune Checkpoint Inhibitors Affecting the Skeleton: A Seminal Case Series,” Journal for ImmunoTherapy of Cancer 6, no. 1 (2018): 104.

[29] K. Wang, Y. Gu, Y. Liao, et al., “PD-1 Blockade Inhibits Osteoclast Formation and Murine Bone Cancer Pain,” Journal of Clinical Investigation 130, no. 7 (2020): 3603-3620.

[30] A. C. Monteiro and A. Bonomo, “CD8(+) T Cells From Experimental in Situ Breast Carcinoma Interfere With Bone Homeostasis,” Bone 150 (2021): 116014.

[31] S. R. Greisen, T. W. Kragstrup, J. S. Thomsen, et al., “The Programmed Death-1 Pathway Counter-Regulates Inflammation-Induced Osteoclast Activity in Clinical and Experimental Settings,” Frontiers in Immunology 13 (2022): 773946.

[32] K. Okamoto and H. Takayanagi, “Osteoimmunology,” Cold Spring Harbor Perspectives in Medicine 9, no. 1 (2019): a031245.

[33] J. Xu, L. Yu, F. Liu, L. Wan, and Z. Deng, “The Effect of Cytokines on Osteoblasts and Osteoclasts in Bone Remodeling in Osteoporosis: A Review,” Frontiers in Immunology 14 (2023): 1222129.

[34] D. H. Yang and M. Y. Yang, “The Role of Macrophage in the Pathogenesis of Osteoporosis,” International Journal of Molecular Sciences 20, no. 9 (2019): 2093.

[35] A. S. Laino, D. Woods, M. Vassallo, et al., “Serum Interleukin-6 and C-Reactive Protein Are Associated With Survival in Melanoma Patients Receiving Immune Checkpoint Inhibition,” Journal for ImmunoTherapy of Cancer 8, no. 1 (2020): e000842.

[36] M. A. Huseni, L. Wang, J. E. Klementowicz, et al., “CD8(+) T Cell-Intrinsic IL-6 Signaling Promotes Resistance to Anti-PD-L1 Immunotherapy,” Cell Reports Medicine 4, no. 1 (2023): 100878.

[37] M. Taki, K. Abiko, M. Ukita, et al., “Tumor Immune Microenvironment During Epithelial-Mesenchymal Transition,” Clinical Cancer Research 27, no. 17 (2021): 4669-4679.

[38] Y. Liang, Q. Bu, W. You, et al., “Single-Cell Analysis Reveals Hypoxia-Induced Immunosuppressive Microenvironment in Intrahepatic Cholangiocarcinoma,” Biochimica et Biophysica Acta—Molecular Basis of Disease 1870, no. 7 (2024): 167276.

[39] Y. Ged, A. Sanchez, S. Patil, et al., “Associations Between Pretreatment Body Composition Features and Clinical Outcomes Among Patients With Metastatic Clear Cell Renal Cell Carcinoma Treated With Immune Checkpoint Blockade,” Clinical Cancer Research 28, no. 23 (2022): 5180-5189.

[40] Z. Lin, W. Wang, Y. Yan, Z. Ma, Z. Xiao, and K. Mao, “A Deep Learning-Based Clinical-Radiomics Model Predicting the Treatment Response of Immune Checkpoint Inhibitors (ICIs)-Based Conversion Therapy in Potentially Convertible Hepatocelluar Carcinoma Patients: A Tumor Marker Prognostic Study,” International Journal of Surgery 111, no. 5 (2025): 3342-3355.

[41] P. You, Q. Li, Y. Lei, et al., “Prediction of Radiosensitivity in Non-Small Cell Lung Cancer Based on Computed Tomography and Tumor Genomics: A Multiple Real World Cohort Study,” Respiratory Research 26, no. 1 (2025): 134.

[42] S. Bakr, O. Gevaert, S. Echegaray, et al., “A Radiogenomic Dataset of Non-Small Cell Lung Cancer,” Scientific Data 5 (2018): 180202.

[43] J. Huang, R. U. Osarogiagbon, D. J. Giroux, et al., “The IASLC Lung Cancer Staging Project: Proposals for the Revision of the N Descriptors in the Forthcoming 9th Edition of the TNM Classification for Lung Cancer,” Journal of Thoracic Oncology 19 (2023).

[44] T. Toshima, T. Yoshizumi, T. Ikegami, et al., “Impact of Osteopenia in Liver Cirrhosis: Special Reference to Standard Bone Mineral Density With Age,” Anticancer Research 38, no. 11 (2018): 6465-6471.

[45] E. A. Eisenhauer, P. Therasse, J. Bogaerts, 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.

[46] S. Bakr, O. Gevaert, S. Echegaray, et al. “Data for NSCLC Radiogenomics (Version 4) [Data Set].” Cancer Imaging Archive, https://doi.org/10.7937/K9/TCIA.2017.7hs46erv.

[47] M. I. Love, W. Huber, and S. Anders, “Moderated Estimation of Fold Change and Dispersion for RNA-seq Data With DESeq2,” Genome Biology 15, no. 12 (2014): 550.

[48] A. Liberzon, C. Birger, H. Thorvaldsdóttir, M. Ghandi, J. P. Mesirov, and P. Tamayo, “The Molecular Signatures Database (MSigDB) Hallmark Gene Set Collection,” Cell Systems 1, no. 6 (2015): 417-425.

[49] A. Subramanian, P. Tamayo, V. K. Mootha, et al., “Gene Set Enrichment Analysis: A Knowledge-Based Approach for Interpreting Genome-Wide Expression Profiles,” PNAS 102, no. 43 (2005): 15545-15550.

[50] P. Charoentong, F. Finotello, M. Angelova, et al., “Pan-Cancer Immunogenomic Analyses Reveal Genotype-Immunophenotype Relationships and Predictors of Response to Checkpoint Blockade,” Cell Reports 18, no. 1 (2017): 248-262.

RIGHTS & PERMISSIONS

2025 The Author(s). MedComm published by Sichuan International Medical Exchange & Promotion Association (SCIMEA) and John Wiley & Sons Australia, Ltd.