Predicting severe radiation pneumonitis in patients with locally- advanced non-small cell lung cancer after thoracic radiotherapy: Development and internal validation of a nomogram based on the clinical, hematological and dose–volume histogram parameters

doi:10.21203/rs.3.rs-4967531/v1

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Research Article

Predicting severe radiation pneumonitis in patients with locally- advanced non-small cell lung cancer after thoracic radiotherapy: Development and internal validation of a nomogram based on the clinical, hematological and dose–volume histogram parameters

https://doi.org/10.21203/rs.3.rs-4967531/v1

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Purpose

Severe radiation pneumonitis (grade≥3 RP) remains an important dose-limiting toxicity after thoracic radiotherapy (RT). This study aimed to investigate risk factors for severe RP in patients with locally-advanced non-small cell lung cancer (NSCLC) after thoracic RT, develop a prediction model to identify high-risk groups and investigate impact of severe RP on overall survival (OS).

Methods

We retrospectively collected clinical, hematological and dosimetric factors from 351 stage-Ⅲ NSCLC patients after thoracic RT between 2018 and 2022. The primary endpoint was development of severe RP. The secondary endpoint was OS. Logistic regression and least absolute shrinkage and selection operator (LASSO) regression analysis were used to identify risk factors of severe RP. Nomogram was generated based on multivariate regression coefficients. Area under the ROC curve (AUC), calibration curve, and decision curve analysis (DCA) were conducted to validate the model. After a long-term follow-up, OS of patients with RP vs. non-RP and mild RP vs. severe RP groups was analyzed by Kaplan‒Meier method.

Results

ILD (p<0.001), percentage of contralateral lung volume receiving≥5Gy (contraV₅) (P=0.013), percentage of ipsilateral lung volume receiving≥20Gy (ipsiV₂₀)(P=0.039), pre-RT derived neutrophil lymphocyte ratio (dNLR) (P=0.015) and post-RT systemic inflammation response index (SIRI) (p=0.001) were showed to be independent predictors of severe RP and were included in the nomogram. ROC curves revealed the AUC of the nomogram was 0.782. Calibration curves showed favorable consistency, and DCA showed satisfactory positive net benefits of the model. Median follow-up time was 19.8 months (1.4-52.9 months), and cases who developed severe RP showed shorter OS than those developed mild RP (P=0.027).

Conclusion

We identified that ILD, contraV₅(>11%), ipsiV₂₀(>45%), pre-RT dNLR (>1.9) and post-RT SIRI (>3.4) could predict severe RP among patients with locally-advanced NSCLC receiving thoracic RT. Combining these indicators, a nomogram was first built and validated, showing its potential value in clinical practice.

Non-small cell lung cancer (NSCLC)

Radiotherapy

Radiation pneumonia

Dosimetric parameter

Peripheral blood biomarkers.

Nowadays, lung cancer is one of the most common malignancies and the leading cause of cancer-related death worldwide^{[1, 2]}, and non-small cell lung cancer (NSCLC) accounts for most cases^[3]. Radiation therapy (RT) has played an important role in the treatment of NSCLC for many years, especially concurrent chemoradiotherapy (CCRT) remains the current standard of care for patients with inoperable locally advanced NSCLC^{[4, 5]}. However, the benefits of RT are occasionally disturbed by relevant adverse effects, among which radiation pneumonitis (RP) is one of the most common thoracic RP-related toxicity^{[6, 7]}, and is one of a main dose-limiting factors that affects the efficacy of RT^[8–12].

RP was been defined as the acute injury stage of radiation-induced lung injury (RILI)^{[13, 14]}, and could be stratified into five grades by the clinical manifestation and imaging performance through Common Terminology Criteria for Adverse Events version 5.0 (CTCAE v. 5.0)^[15]. RP was been reported with an incidence rate varying from 5%-40%^{[7, 8, 10]}, and mild RP consisted majority of cases^{[11, 16]}. RP can lead to chronic respiratory insufficiency, especially for severe RP, i.e., RP of grade 3 or higher, can seriously influence the quality of life of patients, and may even directly threaten the life of patients, leading to treatment-related death^[17], with a mortality as high as 30%^[18].

Therefore, early detection and intervention are crucial for the management of severe RP, and robust markers for the prediction of severe RP is of urgent needed. Various clinical, dosimetric and hematological factors have been found to be associated with the incidence of RP, the former include age, the performance status (PS), smoking status, chronic obstructive pulmonary disease (COPD), pulmonary emphysema, interstitial lung disease (ILD), pulmonary function, concurrent chemotherapy ^{[10, 19–23]}. Among dose-volume histogram (DVH) metrics, gross tumor volume (GTV), mean lung dose (MLD), percent of the lung volume receiving ≥ 5, 20, 30Gy (V₅/V₂₀/V₃₀) and heart dosimetric variables were reported to be related to the occurrence of RP^{[10, 24–27]}. As for peripheral blood leukocyte (PBL) biomarkers, lymphocytes, neutrophil-to-lymphocyte (NLR), derived neutrophil-to-lymphocyte ratio (dNLR), monocyte-to-lymphocyte ratio (MLR) and derived monocyte-to-lymphocyte ratio (dMLR) have previously been reported to be predictors for RP^{[28, 29]}.

However, studies on risk factors and prediction model for severe RP, especially in patients with locally-advanced NSCLC, are limited. Therefore, in order to optimize risk stratification and predict the risk of severe RP more accurately, as well as further guide individualized treatment management decisions, we performed a retrospective study to investigate the potential risk factors for severe RP, including clinical characteristics, DVH parameters and PBL indicators, and aimed at generating a predictive model to quantify risk of severe RP in the population of locally-advanced NSCLC patients treated with thoracic RT. What’s more, we further made a long-term follow-up to track the survival status of patients, and identified the impact of severe RP on survival.

Patients

This retrospective study was approved by the ethics committee of Shanghai Pulmonary Hospital, Shanghai, China. We retrospectively reviewed the medical charts of patients with locally-advanced NSCLC receiving thoracic radiotherapy (total dose > 50 Gy and single dose 2 Gy) between April 2018 and August 2022. The inclusion criteria were as follows: (1) histologically or cytologically proven stage Ⅲ NSCLC, (2) with an Eastern Cooperative Oncology Group performance status (ECOG PS) of 0–2, (3) patients received thoracic radiotherapy from 2018 to 2022, (5) no previous thoracic radiation therapy.

Definition of clinical, DVH and PBL factors

We retrospectively collected clinical, dosimetric and hematological factors for analysis. The clinical factors included age, gender, ECOG PS, smoking status, presence of underlying lung disease (ILD, COPD and pulmonary emphysema), surgery history, total RT dose, chemotherapy history, regimen and sequence, and pulmonary function, which including forced expiratory volume in 1 second (FEV1) and diffusing capacity of the lung for carbon monoxide (DLCO). Pulmonary function testing was done immediately before RT.

The dosimetric factors were collected as follows: GTV, planning tumor volume (PTV), total/contralateral/ipsilateral lung MLD and V₅/₂₀/₃₀, mean heart dose (MHD) and heart V₅₀. V_x was defined as the percentage of lung/heart volume receiving ≥ x Gy. DVH data were obtained from electronic radiation treatment planning documents.

What’s more, we collected hematological factors both pre-radiotherapy (pre-RT) and post-radiotherapy (post-RT), and the latter were defined as the data at one month after the completion of radiotherapy. The collected hematological indicators were composed of white blood cell (WBC) count and its classification count, including the absolute count of neutrophils (NEU), lymphocytes (LYM), monocytes (MON) and eosinophils (EOS), as well as neutrophil-to-lymphocyte ratio (NLR), derived neutrophil-to-lymphocyte ratio (dNLR), monocyte-to-lymphocyte ratio (MLR), derived monocyte-to-lymphocyte ratio (dMLR) and systemic inflammation response index (SIRI). The NLR, dNLR, MLR, dMLR and SIRI were calculated as follows:

Radiotherapy

Three-dimensional conformal radiotherapy (3D-CRT), intensity-modulated radiotherapy (IMRT) or volumetric arc therapy (VMAT) techniques were used to deliver radiotherapy courses. What’s more, four-dimensional computed tomography (4D-CT) scanning of the whole lung was performed to measure intrafraction respiratory movement and create an internal target volume to compensate respiratory motion, with CT scans at intervals of 2.5–5.0 mm and each patient immobilized in the supine position with a vacuum cushion. All radiation treatment plans were generated in Pinnacle treatment planning system, and were delivered using 6–10 MV beams on linear accelerators.

Positron emission tomography/computed tomography (PET/CT) should be obtained preferably within 4 weeks before treatment in the treatment position. Based on fluorodeoxyglucose positron emission tomography (FDG-PET) and the diagnostic CT images, we carefully contoured GTV on the planning CT images, which consisted of the known extent of disease (primary and nodal) on imaging and pathologic assessment, The internal GTV was created using a 4D-CT image. The National Comprehensive Cancer Network (NCCN) guidelines suggest the clinical target volume (CTV) included regions of presumed microscopic extent or dissemination, was expanded by 6-8mm from the internal GTV, and no prophylactic lymph node area was added^[30]. The PTV margin of 5 mm was added for setup uncertainty and respiratory motion. IGRT was applied to real-time monitoring to abate set-up errors. The treatment dose was prescribed to cover 95% of the PTV. The mean lung dose (MLD), the percentage of total lung volume exceeding 20 Gy (V₂₀) and 5 Gy (V₅), as well as the dose constraints for normal tissues (spinal cord, esophagus, and heart) were limited appropriately according to the NCCN guidelines^[30].

Chemotherapy

Adjuvant concurrent or sequential chemotherapy was applied for part of patients based on the NCCN guidelines^[30], and mostly were platinum-based doublets (cisplatin combined with etoposide, vinorelbine or paclitaxel). All the doses and adjustments of the chemotherapy regimen followed the NCCN guidelines^[30].

Endpoint definitions

The primary observation endpoint of this study was grade ≥ 3 RP as defined in CTCAE v5.0^[15], which was graded based on the existence and severity of the clinical symptoms, whether pneumonitis intervention is required, and on the extent of pulmonary fibrosis and accompanying symptoms. RP was diagnosed by professional radiologists and respiratory physicians on the basis of clinical symptoms and changes in CT images, the specific criteria were described in our previous review^[31]. The time to RP was defined as the time interval from the start of radiation treatment to the diagnosis of RP and was calculated using Kaplan-Meier method.

The secondary endpoint was overall survival (OS), which were measured from the start of radiation treatment. The follow-up evaluation was performed 1 month after the completion of thoracic RT, every 3 months for up to two years, then every 6 months for the third year and thereafter. All available follow-up documents were carefully reviewed including clinical records, chest radiographic images, follow-up clinical assessment notes and electronic records until the last follow-up or death of the patients.

Statistical analysis

The predictive model was built as follows: firstly, we measured the impact of clinical characteristics, dose-volume parameters and hematological indicators on the incidence of severe RP using univariable logistic regression model. Secondly, factors with p < 0.05 in univariate analyses were assessed through least absolute shrinkage and selection operator (LASSO) regression analysis to obtain the crucial severe RP-associated factors. Thirdly, a multivariate logistic regression analysis was conducted to select the severe RP-associated factors for establishing a predictive model. Finally, factors with significant predictive value in multivariate analysis were used to build the nomogram. Receiver operating characteristic (ROC) curve analysis was used to establish optimal cut points for continuous variables.

The validation of the nomogram was conducted using the area under the receiver operating characteristic (ROC) curve (AUC), calibration curve (1000 bootstrap resamples) and decision curve analysis (DCA). The ROC curves were used to estimate the discrimination ability of the nomogram and each predictor alone. Calibration curve was used to compare the predicted probability with the observed probability of severe RP. DCA was performed to illustrate the clinical usefulness of the nomogram by quantifying the net benefits at different threshold probabilities.

What’s more, the Kaplan-Meier method was used to estimate OS between patients with non-RP vs. RP, and grade 1–2 RP vs. grade 3 RP.

Statistical analyses were performed with R (Version 4.1.0). All tests were 2-sided, with a P value < 0.05 considered to indicate statistical significance.

Patient characteristics

A total of 351 patients received thoracic radiotherapy between April 2018 and August 2022 were enrolled and a summary of baseline characteristics was listed in Table 1. Of all the 351 patients, 115(32.8%) didn’t experience RP, 236 (67.2%) developed RP (grade 1: n = 91, 25.9%; grade 2: n = 111, 31.6%; grade 3: n = 34, 9.7%; grade 4 and 5: n = 0), and 34 (9.7%) developed severe RP. The median interval from the start of RT to the occurrence of RP was 3.7 months (range, 0.5–28.9 months), and the median occurrence time of severe RP was 3.1 months (range, 1.0-11.6 months).

Table 1

Baseline characteristics of all patients (n = 351)
Characteristics	Number of patients (%)
Age(years), Median (IQR)	65 (58–70)
Gender
Male	284(80.9)
Female	67(19.1)
EOCG PS 0 1 2 Smoking history Yes No Lung disease No ILD COPD Emphysema Surgery Yes No FEV1%, Median (IQR) DLCO%, Median (IQR) Radiotherapy dose(cGy), Median (IQR) Fractionation, Median (IQR)	59(16.8) 271(77.2) 21(6.0) 171(48.7) 180(51.3) 226(64.4) 21(6.0) 17(4.8) 87(24.8) 94(26.8) 257(73.2) 85.1 (70.8–96.8) 91.9 (75.6–106.0) 5800 (5000–6000) 26 (25–30)
Chemotherapy regimen
No chemotherapy	25(7.1)
Include TAX	149(42.5)
Other regimens	177(50.4)
Chemoradiotherapy
CCRT	46(13.1)
SCRT	280(79.8)
RT alone	25(7.1)
GTV (cm³), Median (IQR)	55.1 (28.5-102.6)
Total lung V₅ (%), Median (IQR)	37.8 (32.4–43.8)
Total lung V₂₀ (%), Median (IQR)	21.1 (17.8–24.1)
Total lung V₃₀ (%), Median (IQR)	15.0 (11.4–17.6)
Total lung MLD (cGy), Median (IQR)	1112.5 (910.2-1250.1)
Contralateral lung V₅ (%), Median (IQR)	19.1 (12.7–25.6)
Contralateral lung V₂₀ (%), Median (IQR)	3.8 (1.0-7.9)
Contralateral lung V₃₀ (%), Median (IQR)	1.3 (0.1–3.8)
Contralateral lung MLD (cGy), Median (IQR)	375.0 (263.8-536.9)
Ipsilateral lung V₅ (%), Median (IQR)	58.3 (50.3–68.3)
Ipsilateral lung V₂₀ (%), Median (IQR)	39.2 (33.2–46.2)
Ipsilateral lung V₃₀ (%), Median (IQR)	29.6 (23.5–35.3)
Ipsilateral lung MLD (cGy), Median (IQR)	1891.3 (1585.6-2185.8)
Pre-RT Lymphocytes (10⁶), Median (IQR)	1.6 (1.2-2.0)
Pre-RT Monocytes (10⁶), Median (IQR)	0.5 (0.4–0.7)
Pre-RT Eosinophils (10⁶), Median (IQR)	0.1 (0.1–0.2)
Pre-RT NLR, Median (IQR)	2.6 (1.8–3.7)
Pre-RT dNLR, Median (IQR)	1.8 (1.3–2.5)
Pre-RT MLR, Median (IQR)	0.3 (0.2–0.4)
Pre-RT dMLR, Median (IQR)	0.4 (0.3–0.6)
Pre-RT SIRI (10⁶), Median (IQR)	1.3 (0.8-2.0)
Post-RT Lymphocytes (10⁶), Median (IQR)	0.8 (0.6–1.1)
Post-RT Monocytes (10⁶), Median (IQR)	0.5 (0.3–0.6)
Post-RT Eosinophils (10⁶), Median (IQR)	0.1 (0.1–0.2)
Post-RT NLR, Median (IQR)	4.6 (3.1–6.9)
Post-RT dNLR, Median (IQR)	2.5 (1.8–3.5)
Post-RT MLR, Median (IQR)	0.5 (0.4–0.8)
Post-RT dMLR, Median (IQR)	0.7 (0.5–1.1)
Post-RT SIRI (10⁶), Median (IQR)	2.0 (1.3–3.4)
IQR, interquartile range; ECOG, Eastern Cooperative Oncology Group; PS, performance status; ILD, interstitial lung disease; COPD, chronic obstructive pulmonary disease; FEV1, forced expiratory volume in 1 second; DLCO, diffusing capacity of the lung for carbon monoxide; CCRT, concurrent chemoradiation therapy; SCRT, sequential chemoradiation therapy; GTV, gross target volume; V_x: the percentage of the lung volume that received more than x Gy, respectively; MLD: mean lung dose; NLR: neutrophil lymphocyte ratio; dNLR: derived neutrophil lymphocyte ratio; SIRI: systemic inflammation response index .

This study included 284(80.9%) men and 67(19.1%) women, with a median age of 65 years (range, 40–84 years), and 171(48.7%) patients had a history of smoking. 120 (34.2%) patients had underlying lung disease, including 21(6.0%) with ILD, 17(4.8%) with COPD and 87(24.8%) with emphysema. Totally 326 (92.9%) patients were treated with combined radiation and chemotherapy regimens, and 149 (42.5%) patients using paclitaxel regimen. 46(13.1%) patients received concurrent chemoradiotherapy and 280 (79.8%) patients received sequential chemotherapy, and 94 (26.8%) also underwent surgery.

For all patients, 50–66 Gy were delivered in 1.8–2.0 Gy/fractions.

Univariate, LASSO and multivariate analyses

In order to investigate what factors might differ the incidence of severe RP, univariate Logistic regression analysis was firstly performed, with the optimal ROC cut-off values calculated for continuous variables, and the results are shown in Table 2.

Table 2

Univariate analysis of clinical factors in predicting severe RP
	With severe RP (n = 34)	Without severe RP (n = 317)	Univariate analysis
	N (%)	N (%)	OR (95%CI)	P-value
Clinical factors
Age(years)
> 65	24 (70.6)	156(49.2)	2.477 (1.178–5.584)	0.021 *
≤ 65	10 (29.4)	161(50.8)
Sex
Male	27(79.4)	257(81.1)	0.901 (0.393–2.332)	0.815
Female	7(20.6)	60(18.9)
ECOG PS
2	4(11.8)	17(5.4)	2.353 (0.646–6.859)	0.146
0–1	30(88.2)	300(94.6)
Smoking history
Yes	15(44.1)	156(49.2)	0.815 (0.394–1.656)	0.573
No	19(55.9)	161(50.8)
Lung disease
ILD	9(26.5)	12(3.8)	15.734 (6.409–39.390)	< 0.001
COPD	1(2.9)	16(5.0)	0.570 (0.031–2.935)	0.591
Emphysema	9(26.5)	78(24.6)	1.103 (0.470–2.386)	0.811
Surgery history
Yes	3(8.8)	91(28.7)	0.240 (0.057–0.695)	0.021 *
No	31(91.2)	226(71.3)
Chemotherapy history
Yes	31(91.2)	296(93.4)	0.733 (0.235–3.226)	0.631
No	3(8.8)	21(6.6)
Chemotherapy type
Paclitaxel	18(52.9)	131(41.3)	1.597 (0.785–3.279)	0.196
Others regimen	13(38.2)	165(52.1)
Chemotherapy sequence
CCRT	2(5.9)	44(13.9)	0.388 (0.061–1.343)	0.20
SCRT	29(85.3)	251(79.2)
RT alone	3(8.8)	22(6.9)
FEV1(%)
< 87	21(61.8)	129(40.7)	2.651 (1.136–6.940)	0.032 *
≥87	13(38.2)	188(59.3)
DLCO-SB (%)
<89	13(38.2)	78(24.6)	2.524 (0.986–6.990)	0.060 .
≥89	21(61.8)	239(75.4)
DVH parameters
RT dose (Gy)
> 58	23(67.6)	152(47.9)	2.270 (1.093–4.986)	0.033 *
≤ 58	11(32.4)	165(52.1)
GTV (cm³)
>30	15(44.1)	218(68.8)	0.298 (0.137–0.646)	0.002 **
≤30	19(55.9)	99(31.2)
PTV1(GTV + 1cm) (cm³)
> 202	14(41.2)	201(63.4)	0.353 (0.163–0.756)	0.007 **
≤202	20(58.8)	116(36.6)
PTV2(Actual PTV) (cm³)
> 205	20(58.8)	221(69.7)	0.621 (0.303–1.303)	0.196
≤205	14(41.2)	96(30.3)
PTV1-PTV2 (cm³)
> 15	19(55.9)	101(31.9)	3.095 (1.438–6.972)	0.005 **
≤15	15(44.1)	216(68.1)
Whole lung volume (cm³)
> 2409	21(61.8)	272(85.8)	0.267 (0.126–0.583)	0.001 ***
≤2409	13(38.2)	45(14.2)
Total lungs V₅ (%)
> 41	15(44.1)	118(37.2)	1.331 (0.643–2.713)	0.432
≤ 41	19(55.9)	199(62.8)
Total lung V₂₀ (%)
> 18	20(58.8)	239(75.4)	0.466 (0.226–0.984)	0.040 *
≤ 18	14(41.2)	78(24.6)
Total lung V₃₀ (%)
> 10	33(97.1)	276(87.1)	4.902 (1.012–88.337)	0.118
≤ 10	1(2.9)	41(12.9)
Total MLD (Gy)
> 8	34(100)	276(87.1)	1.4247e + 07 (0-Inf)	0.987
≤8	0(0)	41(12.9)
Contralateral lung V₅ (%)
>11	33(97.1)	254(80.1)	8.185 (1.711-146.936)	0.040 *
≤11	1(2.9)	63(19.9)
Contralateral lung V₂₀ (%)
> 4	20(58.8)	154(48.6)	1.512 (0.743–3.157)	0.259
≤ 4	14(41.2)	163(51.4)
Contralateral lung V₃₀ (%)
> 0.3	28(82.4)	219(69.1)	2.088 (0.893–5.727)	0.114
≥ 0.3	6(17.6)	98(30.9)
Contralateral MLD (Gy)
> 1.9	34(100)	266(83.9)	1.4782e + 07 (0-Inf)	0.986
≤1.9	0(0)	51(16.1)
Ipsilateral lung V₅ (%)
> 62.4	18(52.9)	116(36.6)	1.949 (0.956–4.009)	0.066 .
≤62.4	16(47.1)	201(63.4)
Ipsilateral lung V₂₀ (%)
> 45	15(44.1)	87(27.4)	2.087 (1.002–4.281)	0.045 *
≤45	19(55.9)	230(72.6)
Ipsilateral lung V₃₀ (%)
> 25	28(82.4)	218(68.8)	2.119 (0.906–5.811)	0.107
≤ 25	6(17.6)	99(31.2)
Ipsilateral MLD (Gy)
>19	20(58.8)	134(42.3)	1.738 (0.854–3.631)	0.131
≤19	14(41.2)	183(57.7)
Heart V₅₀ (%)
> 6	14(41.2)	88(27.8)	1.822 (0.866–3.741)	0.105
≤6	20(58.8)	229(72.2)
MHD (Gy)
> 8	21(61.8)	212(66.9)	0.800 (0.390–1.699)	0.549
≤8	13(38.2)	105(33.1)
Hematological indicators
Pre-RT WBC (10⁹/L)
> 6.5	23(67.6)	160(50.5)	2.052 (0.988–4.507)	0.061 .
≤ 6.5	11(32.4)	157(49.5)
Pre-RT NEU (10⁹/L)
> 4.9	17(50.0)	101(31.9)	2.139 (1.043–4.386)	0.037 *
≤ 4.9	17(50.0)	216(68.1)
Pre-RT LYM (10⁹/L)
> 1.7	8(23.5)	139(43.8)	0.394 (0.162–0.861)	0.027 *
≤ 1.7	26(76.5)	178(56.2)
Pre-RT MON (10⁹/L)
> 0.3	31(91.2)	248(78.2)	2.875 (0.988–12.226)	0.088 .
≤ 0.3	3(8.8)	69(21.8)
Pre-RT EOS (10⁹/L)
> 0.1	18(52.9)	152(47.9)	1.221 (0.600-2.504)	0.580
≤ 0.1	16(47.1)	165(52.1)
Pre-RT BASO (10⁹/L)
>0.025	12(35.3)	88(27.8)	1.419 (0.655–2.946)	0.357
≤0.025	22(64.7)	229(72.2)
Pre-RT NLR
> 2.8	20(58.8)	132(41.6)	2.002 (0.983–4.185)	0.058 .
≤ 2.8	14(41.2)	185(58.4)
Pre-RT dNLR
> 1.9	22(64.7)	133(42.0)	2.536 (1.232–5.462)	0.013 *
≤ 1.9	12(35.3)	184(58.0)
Pre-RT SIRI
> 1.6	18(52.9)	110(34.7)	2.117 (1.038–4.357)	0.039 *
≤ 1.6	16(47.1)	207(65.3)
Pre-RT MLR
> 0.3	24(70.6)	176(55.5)	1.923 (0.914–4.336)	0.096 .
≤ 0.3	10(29.4)	141(44.5)
Pre-RT dMLR
> 0.3	30(99.2)	231(72.9)	2.792 (1.063–9.604)	0.061 .
≤ 0.3	4(11.8)	86(27.1)
Post-RT WBC (10⁹/L)
> 5.9	19(55.9)	88(27.8)	3.296 (1.609–6.869)	0.001 **
≤ 5.9	15(44.1)	229(72.2)
Post-RT NEU (10⁹/L)
> 5.3	15(44.1)	50(15.8)	4.216 (1.987–8.841)	< 0.001 ***
≤ 5.3	19(55.9)	267(84.2)
Post-RT LYM (10⁹/L)
> 1.0	7(20.6)	112(35.3)	0.475 (0.185–1.068)	0.090 .
≤ 1.0	27(79.4)	205(64.7)
Post-RT MON (10⁹/L)
> 0.5	21(61.8)	123(38.8)	2.548 (1.245-5.400)	0.012 *
≤ 0.5	13(38.2)	194(61.2)
Post-RT EOS (10⁹/L)
> 0.1	20(58.8)	245(77.3)	0.420 (0.203–0.888)	0.020 *
≤ 0.1	14(41.2)	72(22.7)
Post-RT BASO (10⁹/L)
>0.055	2(5.9)	5(1.6)	3.900 (0.543–18.914)	0.112
≤0.055	32(94.1)	312(98.4)
Post-RT NLR
> 4.5	26(76.5)	158(49.8)	3.271 (1.498–7.930)	0.005 **
≤ 4.5	8(23.5)	159(50.2)
Post-RT dNLR
> 3.3	17(50.0)	86(27.1)	2.686 (1.306–5.531)	0.007 **
≤ 3.3	17(50.0)	231(72.9)
Post-RT SIRI
> 3.4	18(52.9)	70(22.1)	3.970 (1.924–8.269)	< 0.001 ***
≤ 3.4	16(47.1)	247(77.9)
Post-RT MLR
> 0.8	15(44.1)	79(24.9)	2.378 (1.139–4.893)	0.019 *
≤ 0.8	19(55.9)	238(75.1)
Post-RT dMLR
> 0.8	22(64.7)	137(43.2)	2.409 (1.170–5.186)	0.020 *
≤ 0.8	12(35.3)	180(56.8)

In univariable analysis, the following variables were indicated to be significantly associated with severe RP: age > 65 years, ILD, without surgery history, FEV1 < 87.4%, RT dose > 58.3Gy, GTV > 29.6 cm³, PTV1(GTV + 1cm) > 202cm³, PTV1-PTV2 > 15cm³, whole lung volume > 2409.1cm³, total lung V₂₀ > 18%, contralateral lung V₅ > 11%, ipsilateral lung V₂₀ > 45%, pre-RT NEU > 4.9×10⁹/L, pre-RT LYM > 1.7×10⁹/L, pre-RT dNLR > 1.9, pre-RT SIRI > 1.6, pre-RT NMLR > 2.8, post-RT NEU > 5.3×10⁹/L, post-RT MON > 0.5×10⁹/L, post-RT EOS > 0.1×10⁹/L, post-RT NLR > 4.5, post-dNLR > 3.3, post-RT SIRI > 3.4, post-RT MLR > 0.8 and post-RT dMLR > 0.8.

To avoid overfitting, factors with P value < 0.05 were put into LASSO analysis to screen out the crucial predictors (supplementary Fig. 1), where ILD, contralateral lung V5 (ContraV₅) > 11%, ipsilateral V20 (IpsiV₂₀) > 45%, pre-RT dNLR > 1.9 and post-RT SIRI > 3.4 showed significant impact on the incidence of severe RP. Then multivariate logistic regression was conducted on these factors above. In multivariate analysis, ILD (OR:13.903, 95%CI:4.490-45.016, p < 0.001), ContraV₅ (OR: 15.078, 95%CI: 2.670–290.757, p = 0.013), ipsiV₂₀ (OR:2.344, 95%CI: 1.038–5.301, p = 0.039), pre-RT dNLR (OR:2.823, 95%CI: 1.250–6.795, p = 0.015) and post-RT SIRI (OR: 3.756, 95%CI: 1.688–8.481, p = 0.001) were independent prognosticators of severe RP (Table 3). These factors were then utilized in the nomogram building.

Table 3

Multivariate and ROC analysis of the clinical factor, DVH parameters, hematological Indicators and nomogram model in predicting grade ≥ 3 RP
	Multivariate analysis		ROC curve
	OR (95%CI)	P-value	AUC (95% CI)	P-value
Clinical factors
ILD	13.903 (4.490-45.016)	< 0.001	0.613 (0.537–0.689)	< 0.001
DVH parameters
ContraV₅ > 11%	8.925 (1.728-164.761)	0.038	0.585 (0.548–0.621)	0.008
IpsiV₂₀ > 45%	2.344 (1.038–5.301)	0.039	0.583 (0.495–0.672)	0.021
PBL markers
Pre-RT dNLR > 1.9	2.823 (1.250–6.795)	0.015	0.614 (0.528-0.700)	0.006
Post-RT SIRI > 3.4	3.756 (1.688–8.481)	0.001	0.654 (0.566–0.743)	< 0.001
Nomogram*	-	-	0.782 (0.701–0.864)	< 0.001

Development and validation of the nomogram

Based on the multivariate logistic regression coefficients, a predictive model was visually presented as a nomogram (Fig. 1). The ROC curves of ILD, contra V₅ > 11%, ipsiV₂₀ > 45%, pre-RT dNLR > 1.9, post-RT SIRI > 3.4, and the nomogram are shown in Fig. 2A. The predictive model showed an excellent AUC of 0.782 (95%CI: 0.701–0.864) by ROC, which was much higher than each parameter alone (ILD: 0.613, 95%CI: 0.537–0.689; ContraV5 > 11%: 0.585, 95%CI: 0.548–0.621; IpsiV20:0.583, 95%CI: 0.495–0.672; Pre-RT dNLR > 1.9: 0.614, 95%CI: 0.528-0.700; Post-RT SIRI > 3.4: 0.654, 95%CI: 0.566–0.743 (Table 3). Also, a calibration curve showed favorable consistency between the predicted severe RP and the actual observation (Fig. 2B), and DCA showed satisfactory positive net benefits of the nomogram among most of the threshold probabilities, indicating favorable potential clinical effect of the model (Fig. 2C).

Severe RP and survival

The influence of RP on survival outcomes was further investigated in these patients. The median follow-up duration was 19.8 months (range, 1.4 to 52.9 months). At the time of data cut-off, 46 patients were lost to follow-up, and 62 patients (20.3%) had died. All patients (n = 305) were divided into the non-RP group (n = 95) and RP group (n = 210). The RP group was further subdivided into severe RP group (n = 32) and mild RP group (n = 178). As shown in Fig. 3A, the median OS was not reached for the RP group and the non-RP group, and there was no significant difference in OS between these two groups (p = 0.334). And the median OS was 30.8 months for severe RP group, while was not reached for mild RP subgroup. Compared with patients with mild RP, patients with severe RP performed a worse OS (Fig. 3B) (p = 0.027).

At present, severe RP is one of the most important clinically relevant toxicity of thoracic radiation for patients with locally-advanced NSCLC, which not only affect the following treatment of patients, but also severely influenced the life quality and long-term survival. Thus, reducing the occurrence of severe RP is a critical goal for clinicians. While nowadays, there were still no effective method to predict the incidence of severe RP. In the present study, we collected data from 351 patients with locally-advanced NSCLC patients and after a long-term follow-up of up to 52.9 months, our data indicated that subclinical ILD, contralateral V5 > 11%, ipsilateralV20 > 45%, pre-RT dNLR > 1.9 and post-RT SIRI > 3.4 were the independent prognosticators of severe RP among patients with locally-advanced NSCLC receiving thoracic RT. The internal validation of the constructed nomogram demonstrated its superiority compared with any single hematological, dosimetric or clinical factor alone. These findings can be used to accurately identify patients with high risk for severe RP, and indicated that individualized and precise radiotherapy regimens can significantly reduce the occurrence of severe RP and can improve the prognosis of RP and the quality of life of patients.

Compared to other similar researches^{[29, 32, 33]}, it must be pointed out that to the best of our knowledge, our study is the first to systematically integrate clinical factors, peripheral blood biomarkers and dose-volume parameters to develop a predictive model for the occurrence of severe RP in such a large sample of patients with locally-advanced NSCLC treated with thoracic radiotherapy.

Our study reported that 9.7% patients developed severe RP, which was in accordance with those reported in previous studies (about 5-11.7%) ^[34–36]. And in our study, severe RP conferred a worse overall survival comparing with mild RP (30.8m vs. NR, p = 0.027), similar conclusions were reached by other recent studies^{[37, 38]}, while there was no significant difference between RP and non-RP patients (20.4m vs. 17.6m, p = 0.330). It underlined that early detection and timely intervention of severe RP is of great importance, which could help prolong the survival of patients.

We confirmed that patients with ILD intended to have higher risk of severe RP, it was in line with our preliminary studies ^{[39, 40]}, and similar results were also in reported by other researches^{[23, 41]}. Due to similar mechanisms, lung cancer (LC) patients have a high incidence of ILD, and ILD patients are also prone to develop lung cancer^{[42, 43]}. Thoracic radiotherapy can be a choice for LC-ILD patients, while radiotherapy is contra-indicated in severe ILD, producing RP rates of up to 43%^[44]. So clinical radiotherapy decisions must be cautious about the risk of severe RP in patients with ILD, and more conservative limits of lung dose should be used with a diagnosis or radiologic evidence of ILD, and specific measures should be taken in the early period of RP.

For patients with locally advanced NSCLC treated with definitive chemo-radiotherapy, the NCCN guideline recommended lung dose–volume constraints for conventionally fractionated RT: total lung V₂₀ ≤ 35–40% and MLD ≤ 20 Gy^[5], while there were there is still no principle or recommendation for evidence-based medicine for the dose limits of contralateral or ipsilateral lung dose. In present study, contralateral V5(> 11%) and ipsilateral V20(> 45%) showed significant associations with severe RP incidence. Bongers’s research have shown that contraV5 were predictor for grade ≥ 3 RP^[45], while the optimal cutoff point has not been confirmed. And Zhao’s research also indicated that contralateral V5 were related to the clinical outcome of patients with severe RP (p = 0.057)^[33]. One study by Ramella showed that ipsiV20 could effectively dividing patients into high-risk and low-risk groups for RP with the threshold value as 52%^[26]. And Agrawal’s study found that ipsiV20 were significantly correlating with RP on univariate analysis, and mean ipsiV20 were 60% for patients with RP^[46]. The threshold of ipsiV20 in our study is lower than in mentioned studies, it may because with the development of multidisciplinary therapy, systemic administration may increase the occurrence of RP, resulting in a decrease in the threshold of ipsilateral lung dose.

A growing body of evidence indicates that blood-based biomarkers can be used to predict radiation-related toxicity ^[47]. Based on our analysis in present study, we found pre-RT dNLR greater than 1.9 and post-RT SIRI greater than 3.4 were the most significant risk hematological biomarker for the development of severe RP. For dNLR, several researches have shown its relation to worse OS and other treatment toxicities, for example, Hsiang found that elevated pre-RT dNLR is associated with worse OS and development of liver toxicity for patients with hepatocellular carcinoma after stereotactic body radiotherapy (SBRT), and dNLR ≥ 1.9 was an optimal cut-off value for determining liver toxicity risk^[48], which was exactly consistent with our findings. Cox’s research showed that an elevated pre-treatment dNLR was an independent prognostic biomarker for OS and PFS in oesophageal cancer patients treated with definitive CRT with the cutoff of 2^[49], which was close to our data. Although the potential mechanisms are unclear, it might be due to that RP is a kind of immune-mediated hypersensitive pneumonia actually^[50], and T lymphocyte subsets play a dominant role in the cellular immune response and may be involved in RP^[51]. What’s more, patients with lower lymphocyte count have been shown to have negative impact on the immune system, leading to the development of infections^[52]. For SIRI, our previous study has demonstrated that pretreatment SIRI are independent predictors of OS in stage Ⅲ NSCLC^[53]. As previously reported, decreased lymphocyte count after RT may be a clinical indicator in the occurrence of RP^[29], and even the severity of RP was associated with the degree of lymphocyte decrease^[54], and the potential mechanism of lymphopenia after RT might be the effect of local irradiation of circulating lymphocyte in the blood pool^[55]. And in the early phase of RP, after alveolar and interstitial edema is formed, then inflammatory cells outside like monocyte-derived pulmonary macrophages and neutrophils are recruited and accumulated here to effect action^[56]. Thus, the relationship between post-RT SIRI and RP are possibly related to different changes in immune cells, including the decrease of lymphocytes and the increase of neutrophils and monocytes after RT.

Several limitations should be mentioned here. Firstly, due to its retrospective nature, selective bias existed in the present study, thus more prospective studies are necessary in the future. Secondly, although the internal validation showed a relatively excellent AUC (0.782) of the present predictive model, the result would be more convincing if it had been verified by an external validation, and the model needs to be further modified and verified in future studies before applied to the clinic. What’s more, there are several biomarkers including the vitronectin (VTN) and the single nucleotide polymorphisms (SNPs) have also been investigated and considered as predictors of RP recently^{[57, 58]}, hence from the perspective of precision medicine, a more comprehensive prediction model for severe RP combining the individual genomic information, dosimetric, hematological and clinical parameters should be developed in the future.

In conclusion, early detection and early intervention of severe RP is of great importance due to the impact on long-term outcome. In the era of multidisciplinary comprehensive treatment for locally advanced NSCLC, lung dose constrains should be more rigorous, which would exactly affect the incidence and severity of RP. Moreover, biomarkers in peripheral blood could predict severe RP in some extent, and could be used to accurately identify high-risk patients. The multivariate analysis identified the ILD, contraV₅ (> 11%), ipsiV₂₀ (> 45%), pre-RT (> 1.9) and post-RT SIRI (> 3.4) as independent risk factors for severe RP in patients with locally advanced NSCLC receiving thoracic RT. A predictive nomogram was built and its efficiency confirmed by internal validation. Although needing further verification, our work still has a value for identifying patients at high risk of severe RP and evaluation of treatment plans.

NSCLC

non-small cell lung cancer

radiation therapy

CCRT

concurrent chemoradiotherapy

radiation pneumonitis

RILI

radiation-induced lung injury

overall survival

CTCAE

common Terminology Criteria for Adverse Events

NCCN

national comprehensive cancer network

ECOG-PS

eastern cooperative oncology group performance status

COPD

chronic obstructive pulmonary disease

ILD

interstitial lung disease

FEV1

forced expiratory volume in 1 second

DLCO

diffusing capacity of the lung for carbon monoxide

DVH

dose-volume histogram

GTV

gross tumor volume

CTV

clinical tumor volume

PTV

planning tumor volume

MLD

mean lung dose

MHD

mean heart dose

percentage of lung/heart volume receiving ≥ x Gy

PBL

peripheral blood leukocyte

NLR

neutrophil-to-lymphocyte

dNLR

derived neutrophil-to-lymphocyte ratio

MLR

monocyte-to-lymphocyte ratio

dMLR

derived monocyte-to-lymphocyte ratio

SIRI

systemic inflammation response index

WBC

white blood cell

NEU

neutrophil

LYM

lymphocyte

MON

monocyte

EOS

eosinophil

3D-CRT

three-dimensional conformal radiotherapy

IMRT

intensity-modulated radiotherapy

VMAT

volumetric arc therapy

4D-CT

four-dimensional computed tomography

PET/CT

positron emission tomography/computed tomography

FDG-PET

fluorodeoxyglucose positron emission tomography

LASSO

least absolute shrinkage and selection operator

ROC

receiver operating characteristic

AUC

area under the ROC curve

DCA

decision curve analysis

Ethical approval declaration:

The study was approved by the Ethic Committee of Shanghai Pulmonary Hospital (No. L22-357).

Human Ethics and Consent to Participate declarations:

not applicable.

Clinical trial number:

not applicable.

Consent to publish:

not applicable.

Funding:

This work was supported by the 2023 Development Fund of Discipline-Department of Radiotherapy and the 2021 Shanghai Municipal Science and Technology Commission Technical Standards Project (No. 21DZ2201900).

Availability of data and materials:

not applicable.

Conflict of interest statement:

No actual or potential conflicts of interest exist.

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Predicting severe radiation pneumonitis in patients with locally- advanced non-small cell lung cancer after thoracic radiotherapy: Development and internal validation of a nomogram based on the clinical, hematological and dose–volume histogram parameters

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Abstract

Figures

Introduction

Methods and Materials

Patients

Definition of clinical, DVH and PBL factors

Radiotherapy

Chemotherapy

Endpoint definitions

Statistical analysis

Results

Patient characteristics

Univariate, LASSO and multivariate analyses

Development and validation of the nomogram

Severe RP and survival

Discussion

Conclusion

Abbreviations

Declarations

References

Additional Declarations

Supplementary Files

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