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. 2021 Jan;10(1):67-74.
doi: 10.1002/psp4.12578. Epub 2020 Dec 21.

Longitudinal Tumor Size and Neutrophil-to-Lymphocyte Ratio Are Prognostic Biomarkers for Overall Survival in Patients With Advanced Non-Small Cell Lung Cancer Treated With Durvalumab

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Longitudinal Tumor Size and Neutrophil-to-Lymphocyte Ratio Are Prognostic Biomarkers for Overall Survival in Patients With Advanced Non-Small Cell Lung Cancer Treated With Durvalumab

Sergey Gavrilov et al. CPT Pharmacometrics Syst Pharmacol. 2021 Jan.

Abstract

Therapy optimization remains an important challenge in the treatment of advanced non-small cell lung cancer (NSCLC). We investigated tumor size (sum of the longest diameters (SLD) of target lesions) and neutrophil-to-lymphocyte ratio (NLR) as longitudinal biomarkers for survival prediction. Data sets from 335 patients with NSCLC from study NCT02087423 and 202 patients with NSCLC from study NCT01693562 of durvalumab were used for model qualification and validation, respectively. Nonlinear Bayesian joint models were designed to assess the impact of longitudinal measurements of SLD and NLR on patient subgrouping (by Response Evaluation Criteria in Solid Tumors 1.1 criteria at 3 months after therapy start), long-term survival, and precision of survival predictions. Various validation scenarios were investigated. We determined a more distinct patient subgrouping and a substantial increase in the precision of survival estimates after the incorporation of longitudinal measurements. The highest performance was achieved using a multivariate SLD and NLR model, which enabled predictions of NSCLC clinical outcomes.

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Conflict of interest statement

Sergey Gavrilov, Kirill Zhudenkov, and Kirill Peskov are employees of M&S Decisions LLC, a modeling consultancy contracted by AstraZeneca. All other authors declared no competing interests for this work.

Figures

Figure 1
Figure 1
Comparison of training and validation data sets: (a) Kaplan–Meier estimates. (b) and (c) ‐ marginal SLD and NLR profiles computed using a moving average within a 2‐month time interval respectively. Mean estimates with 95% confidence intervals are shown. NLR, neutrophil‐to‐lymphocyte ratio; SLD, sum of the longest diameters.
Figure 2
Figure 2
Simulated vs. observed survival for Response Evaluation Criteria in Solid Tumors–based subgroups: (a) COX model, (b) JM SLD model, (c) and multivariate JM SLD&NLR model. JM simulations made use of 3 months of longitudinal SLD and NLR data. Ranges (in various colors) represent the 50% range for the simulated survival curves. Solid lines represent simulated median survival. Dashed lines represent observed Kaplan–Meier estimates for subgroups of patients. COX, Cox proportional hazards model; CR, complete response; JM, joint model; NLR, neutrophil‐to‐lymphocyte ratio; PD, progressive disease; PR, partial response; SD, stable disease; SLD, sum of the longest diameters.
Figure 3
Figure 3
Estimated survival with 95% confidence intervals for two simulated patients with matching baseline SLD and NLR values: good vs. poor prognosis represented by biomarker changes over 3 months after start of treatment. (a) SLD is either increased or decreased, and NLR remains constant. (b) NLR is either increased or decreased, and SLD remains constant, (c) Both SLD and NLR are either increased or decreased. NLR, neutrophil‐to‐lymphocyte ratio; SLD, sum of the longest diameters.

References

    1. Siegel, R.L. , Miller, K.D. & Jemal, A. Cancer statistics. CA Cancer J. Clin. 69, 7–34 (2019). - PubMed
    1. Schrank, Z. et al Current molecular‐targeted therapies in NSCLC and their mechanism of resistance. Cancers (Basel) 10, 224 (2018). - PMC - PubMed
    1. Rolfo, C. et al Immunotherapy in NSCLC: a promising and revolutionary weapon. Adv. Exp. Med. Biol. 995, 97–125 (2017). - PubMed
    1. Remon, J. et al Advanced‐stage non‐small cell lung cancer: advances in thoracic oncology 2018. J. Thoracic Oncol. 14, 1134–1155 (2019). - PubMed
    1. Okamoto, I. et al Real world treatment and outcomes in EGFR mutation‐positive non‐small cell lung cancer: Long‐term follow‐up of a large patient cohort. Lung Cancer 117, 14–19 (2018). - PubMed

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