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. 2022 Jan 4;29(1):193-208.
doi: 10.3390/curroncol29010019.

Impact of Pre-Treatment NLR and Other Hematologic Biomarkers on the Outcomes of Early-Stage Non-Small-Cell Lung Cancer Treated with Stereotactic Body Radiation Therapy

Marina Aduquaye  1 , Sheen Dube  1   2 , Bashir Bashir  1 , Amitava Chowdhury  1 , Naseer Ahmed  1 , Ahmet Leylek  1 , Julian Kim  1 , Pascal Lambert  3 , Oliver Bucher  3 , William Hunter  1   4 , Gokulan Sivananthan  1   4 , Rashmi Koul  1 , Shrinivas Rathod  1
Affiliations

Impact of Pre-Treatment NLR and Other Hematologic Biomarkers on the Outcomes of Early-Stage Non-Small-Cell Lung Cancer Treated with Stereotactic Body Radiation Therapy

Marina Aduquaye et al. Curr Oncol. .

Abstract

Introduction: We evaluated the association of pre-treatment immunologic biomarkers on the outcomes of early-stage non-small-cell lung cancer (NSCLC) patients treated with stereotactic body radiation therapy (SBRT).

Materials and methods: In this retrospective study, all newly diagnosed early-stage NSCLC treated with SBRT between January 2010 and December 2017 were screened and included for further analysis. The pre-treatment neutrophil-lymphocyte ratio (NLR), monocyte lymphocyte ratio (MLR), and platelet-lymphocyte ratio (PLR) were calculated. Overall survival (OS) and recurrence-free survival (RFS) were estimated by Kaplan-Meier. Multivariable models were constructed to determine the impact of different biomarkers and the Akaike information criterion (AIC), index of adequacy, and scaled Brier scores were calculated.

Results: A total of 72 patients were identified and 61 were included in final analysis. The median neutrophil count at baseline was 5.4 × 109/L (IQR: 4.17-7.05 × 109/L). Median lymphocyte count was 1.63 × 109/L (IQR: 1.29-2.10 × 109/L), median monocyte count was 0.65 × 109/L (IQR: 0.54-0.83 × 109/L), median platelet count was 260.0 × 109/L (IQR: 211.0-302.0 × 109/L). The median NLR was 3.42 (IQR: 2.38-5.04), median MLR was 0.39 (IQR: 0.31-0.53), and median PLR was 156.4 (IQR: 117.2-197.5). On multivariable regression a higher NLR was associated with worse OS (p = 0.01; HR-1.26; 95% CI 1.04-1.53). The delta AIC between the two multivariable models was 3.4, suggesting a moderate impact of NLR on OS. On multivariable analysis, higher NLR was associated with poor RFS (p = 0.001; NLR^1 HR 0.36; 0.17-0.78; NLR^2 HR-1.16; 95% CI 1.06-1.26) with a nonlinear relationship. The delta AIC between the two multivariable models was 16.2, suggesting a strong impact of NLR on RFS. In our cohort, MLR and PLR were not associated with RFS or OS in multivariable models.

Conclusions: Our study suggests NLR, as a biomarker of systemic inflammation, is an independent prognostic factor for OS and RFS. The nonlinear relationship with RFS may indicate a suitable immunological environment is needed for optimal SBRT action and tumoricidal mechanisms. These findings require further validation in independent cohorts.

Keywords: biomarkers; early-stage lung cancer; stereotactic body radiation therapy.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Pretreatment distribution of neutrophils (A), lymphcytes (B), monocytes (C), and platelet (D).
Figure 1
Figure 1
Pretreatment distribution of neutrophils (A), lymphcytes (B), monocytes (C), and platelet (D).
Figure 2
Figure 2
Risk of death by NLR.
Figure 3
Figure 3
Kaplan–Meier curves for OS by NLR (A), MLR (B), and PLR (C) using predicted values at the 10th, 50th, and 90th percentile of predictors.
Figure 4
Figure 4
Risk of RFS by NLR.
Figure 5
Figure 5
Kaplan–Meier curves for RFS by NLR (A), MLR (B), and PLR (C) using predicted values at the 10th, 50th, and 90th percentile of predictors.
Figure 5
Figure 5
Kaplan–Meier curves for RFS by NLR (A), MLR (B), and PLR (C) using predicted values at the 10th, 50th, and 90th percentile of predictors.
Figure 6
Figure 6
Risk of LRFS by NLR.
Figure 7
Figure 7
Kaplan–Meier curves for LRFS by NLR (A), MLR (B), and PLR (C) using predicted values at the 10th, 50th, and 90th percentile of predictors.
Figure 7
Figure 7
Kaplan–Meier curves for LRFS by NLR (A), MLR (B), and PLR (C) using predicted values at the 10th, 50th, and 90th percentile of predictors.
See this image and copyright information in PMC

References

    1. Chang J.Y., Senan S., Paul M.A., Mehran R.J., Louie A.V., Balter P., Groen H.J.M., E McRae S.E., Widder J., Feng L., et al. Stereotactic ablative radiotherapy versus lobectomy for operable stage I non-small-cell lung cancer: A pooled analysis of two randomised trials. Lancet Oncol. 2015;16:630–637. doi: 10.1016/S1470-2045(15)70168-3. - DOI - PMC - PubMed
    1. Timmerman R., Paulus R., Galvin J., Michalski J., Straube W., Bradley J., Fakiris A., Bezjak A., Videtic G., Johnstone D., et al. Stereotactic body radiation therapy for inoperable early stage lung cancer. JAMA. 2010;303:1070–1076. doi: 10.1001/jama.2010.261. - DOI - PMC - PubMed
    1. Brown J.M., Carlson D.J., Brenner D.J. The Tumor radiobiology of SRS and SBRT: Are more than the 5 Rs involved? Int. J. Radiat. Oncol. 2014;88:254–262. doi: 10.1016/j.ijrobp.2013.07.022. - DOI - PMC - PubMed
    1. Reese A.S., Feigenberg S.J., Husain A., Webb T., Hausner P.F., Edelman M., Feliciano J., Tkaczuk K.H., Sharma N.K. Stereotactic Ablative Radiotherapy (SABR): Impact on the immune system and potential for future therapeutic modulation. Mol. Cell. Pharmacol. 2013;5:19–25. - PMC - PubMed
    1. Song C.W., Kim M.-S., Cho L.C., Dusenbery K., Sperduto P.W. Radiobiological basis of SBRT and SRS. Int. J. Clin. Oncol. 2014;19:570–578. doi: 10.1007/s10147-014-0717-z. - DOI - PubMed