Some patients with non-small cell lung cancer (NSCLC) experience early relapse within 2 years post-surgery. Screening patients who are prone to recurrence is crucial. This study aimed to determine factors influencing early recurrence within 2 years of surgery for stage IA-IIA NSCLC and to establish a prediction model.

We retrospectively analyzed the hematological indices and imaging indicators of patients with stage IA-IIA NSCLC who underwent surgery at our hospital, and relevant clinical data were obtained through long-term follow-up from September 2019 to September 2020. Least absolute shrinkage and selection operator (LASSO) regression and univariate and multivariate Cox regression analyses were used to identify high-risk factors influencing postoperative recurrence, establish a predictive model, and construct a nomogram associated with recurrence-free survival.

Among 186 patients (90 male and 96 female), 29 (15.6%) experienced recurrence or metastasis during the follow-up period. Univariate analysis identified several significant factors, including tumor size, direct bilirubin, indirect bilirubin, albumin, globulin, serum creatinine, platelet-lymphocyte ratio, lymphocyte-monocyte ratio, prognostic nutrition index, albumin-alkaline phosphatase ratio, marginal lobulation, air bronchogram sign, pathological type of squamous cell carcinoma, tumor stage IB, and solid nodules. LASSO regression was used to further select variables and construct a multivariate Cox model showing globulin levels, air bronchogram signs, and solid nodules as independent prognostic factors for early recurrence within 2 years in patients with stage IA-IIA NSCLC. The Cox model stratified patients into high- and low-risk groups and was validated by Kaplan-Meier survival analysis, which demonstrated that high-risk patients had a significantly lower survival rate than low-risk patients, demonstrating the robust discriminative power of the predictive model.

Globulin content, air bronchogram signs, and solid nodules were independent prognostic factors for early recurrence within 2 years in patients with stage IA-IIA NSCLC. The proposed model, developed based on the above factors and the albumin-alkaline phosphatase ratio, can effectively predict recurrence risk, potentially aiding clinicians in quantifying prognostic risk, making personalized survival assessments, and devising the most effective treatment plans.

Stereotactic body radiation therapy is indicated in cases of early inoperable lung cancer and surgical rejection, and it is also an option for oligometastatic, recurrent, and/or relapsing tumours. The aim of this study was to analyse the incidence of different patterns of radiological changes on CT scans, correlate their occurrence with risk factors, and analyse the usefulness of imaging information to predict treatment outcome in terms of local progression-free survival.

A retrospective review was carried out on the data from 104 patients who received lung stereotactic body radiation therapy between 2014 and 2022. A first check-up visit was carried out a month after treatment. Visits were then performed every 3 to 4months during the first year, with imaging tests (CT or PET), and every 4 to 6months after the first year. Acute radiological changes were defined as those occurring in the first 6months and chronic radiological changes as those occurring starting from 6months onwards following treatment.

Acute radiological changes were detected in 44.44 % of the patients, with up to 86 % of them appearing chronically. The modified conventional fibrosis pattern was the most prevalent. Having received lung thoracic radiotherapy and irradiation of tumours located in peripheral regions significantly increases the likelihood of chronic radiological changes appearing. Fifteen patients underwent further tests such as a PET scan for suspected local progression after the appearance of chronic changes, of which 11 were positive. No association was identified between the occurrence of either acute or chronic radiological changes with worsened survival or a higher percentage of local progression.

Proper knowledge of the different patterns of radiological changes secondary to lung stereotactic body radiation therapy and their dynamics over time is necessary to discern between a benign pathology and progression.

The debate regarding the accuracy of radiobiological models for local control (LC) prediction in lung cancer patients undergoing stereotactic body radiation therapy (SBRT) remains unresolved. The study seeks to externally validate the predictive efficacy of radiobiological models using single-institutional SBRT database.

The cohort comprised 153 patients diagnosed with primary or metastatic lung cancer who underwent SBRT. The study employed three radiobiological models to estimate the probability of 2-year LC, including the Liu model, Klement model, and Ohri model. Furthermore, the likelihood of 3-year LC was predicted using the Liu model, Klement model, Gucken model, and Santiago model. The performance of the prediction models was assessed through the AUC values of the receiver operating characteristic (ROC) curve and the calibration plots.

Local recurrence was observed in 38.6% of patients (59/153) within two years, and in 43.1% (66/153) within three years after the radiotherapy. The ROC curves indicated discriminative power for all the 2-year and 3-year models, with the exception of the Klement model. The Ohri model showed a significantly improved discriminative ability than the Klement model for 2-year prediction, while it was not statistically significant when compared to the Liu model. However, no significant differences were found among the four models in terms of 3-year LC prediction. The calibration plots, using the Hosmer-Lemeshow goodness-of-fit test, confirmed that the predicted probabilities of the models were in agreement with the actual observation with P>0.05, except for the 2-year LC prediction using the Klement model.

Considering the balance between prediction accuracy and model simplicity, it is recommended to utilize the Ohri model for 2-year LC prediction and either the Gucken model or Santiago model for 3-year LC prediction.

The study aims to investigate whether including the inflammation-related parameters would enhance the accuracy of a nomogram for local control (LC) prediction in lung cancer patients undergoing stereotactic body radiation therapy (SBRT).

158 primary or metastatic lung cancer patients treated with SBRT were retrospectively analyzed. The clinical, dosimetric and inflammation-related parameters were collected for the Cox regression analysis. The ACPB model was constructed by employing the clinical and dosimetric factors. And the ACPBLN model was established by adding the inflammation-related factors to the ACPB model. The two models were compared in terms of ROC, Akaike Information Criterion (AIC), C-index, time-dependent AUC, continuous net reclassification index (NRI), integrated discrimination improvement (IDI), calibration plots and decision curve analysis (DCA).

Multivariate Cox regression analysis revealed that six prognostic factors were independently associated with LC, including age, clinical stage, planning target volume (PTV) volume, BED of the prescribed dose (BEDPD), the lymphocyte count and neutrocyte count. The ACPBLN model performed better in AIC, bootstrap-corrected C-index, time-dependent AUC, NRI and IDI than the ACPB model. The calibration plots showed good consistency between the probabilities and observed values in the two models. The DCA curves showed that the ACPBLN nomogram had higher overall net benefit than the ACPB model across a majority of threshold probabilities.

The inflammation-related parameters were associated with LC for lung cancer patients treated with SBRT. The inclusion of the inflammation-related parameters improved the predictive performance of the nomogram for LC prediction.

Background: After stereotactic body radiation therapy (SBRT) for lung tumors, follow-up CT scans remain a pitfall. The early detection of local relapse is essential to propose a new treatment. We aim to create a local recurrence predictive score using pre- and post-therapeutic imaging criteria and test it on a validation cohort. Methods: Between February 2011 and July 2016, lung tumors treated by SBRT with available pretreatment fluorine-18-fluorodeoxyglucose positron emission tomography (FDG-PET) and follow-up CT scans were retrospectively analyzed. The risk factors associated with relapse were identified by univariate logistic regression on a train cohort. The score was created using these factors, merging clinical and imaging criteria associated with local relapse, and then tested on an independent validation cohort. Overall and local relapse-free survival at 1 and 3 years were recorded. Results: Twenty-eight patients were included in the train cohort and ten in the derivation cohort (male 74%, median age 70 ± 12 years). Five variables significantly associated with local recurrence (female gender; sequential enlargement; craniocaudal growing; bulging margins; standardized uptake value (SUVmax > 5.5)) were combined to create the score on five points. With the threshold >2.5/5, the sensitivity and specificity of the score on the validation cohort were 100% and 88%, respectively. Overall survival and local relapse-free survival at 1 and 3 years were 89% and 42%, and 89% and 63%, respectively. Conclusion: The local recurrence risk score created has high sensitivity (100%) and specificity (88%), upon independent validation cohort, to detect local relapse. This score is easy to use in daily clinical practice.

Non-small cell lung cancer (NSCLC) is a heterogeneous disease accounting for approximately 85% of all lung cancers. Only 17% of patients are diagnosed at an early stage. Treatment is multidisciplinary and radiotherapy plays a key role in all stages of the disease. More than 50% of patients with NSCLC are treated with radiotherapy (curative-intent or palliative). Technological advances-including highly conformal radiotherapy techniques, new immobilization and respiratory control systems, and precision image verification systems-allow clinicians to individualize treatment to maximize tumor control while minimizing treatment-related toxicity. Novel therapeutic regimens such as moderate hypofractionation and advanced techniques such as stereotactic body radiotherapy (SBRT) have reduced the number of radiotherapy sessions. The integration of SBRT into routine clinical practice has radically altered treatment of early-stage disease. SBRT also plays an increasingly important role in oligometastatic disease. The aim of the present guidelines is to review the role of radiotherapy in the treatment of localized, locally-advanced, and metastatic NSCLC. We review the main radiotherapy techniques and clarify the role of radiotherapy in routine clinical practice. These guidelines are based on the best available evidence. The level and grade of evidence supporting each recommendation is provided.

Post-treatment surveillance for local recurrence (LR) following SABR can include both fluorodeoxyglucose-positron emission tomography (FDG-PET) and computed tomography (CT). Radiation-induced lung injury (RILI) shares a similar appearance to LR after treatment making the detection of LR on imaging difficult for clinicians. We aimed to summarise radiological features of CT and FDG-PET predicting LR, and to evaluate radiomics as another tool for detecting LR.

We searched MEDLINE, EMBASE and PubMed databases for published studies and Web of Science, Wiley Online and Science Direct databases for conference abstracts that had patient populations with NSCLC and reported post-SABR radiological features of FDG-PET or CT and radiomics from either FDG-PET or CT. Studies for inclusion were independently reviewed by two authors.

Across 32 relevant studies, the incidence of LR was 13% (222/1726). On CT, certain gross radiological appearances, and kinetic features of changes in size, diameter, volume or 3 consecutive rises in volume of mass-like consolidation are suggestive of LR. Particular regard should be made for the presence of any ≥3 high-risk features (HRF) on CT or the individual HRF of enlarging opacity at ≥12 month's post-SABR as being highly suspicious of LR. On FDG-PET a relative reduction of <5% of SUV_max from baseline in the first 12 months or cut-offs of SUV_max >5 and SUV_mean >3.44 after 12 months can indicate LR. There is limited evidence available to corroborate radiomic features suggestive of LR.

This research has identified common features of LR compared to RILI which may aid in early and accurate detection of LR post-SABR; further research is required to validate these findings.