Risk of conversion and severe postoperative complications in older patients with non-small cell lung cancer and a history of COVID-19: a population-based study

Introduction

Healthcare systems throughout the world have faced significant disruptions since the onset of the coronavirus disease 2019 (COVID-19) pandemic, originally caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in 2019 (1). By September 2024, over 776 million confirmed cases and more than 7 million deaths had been reported worldwide, with the social and economic repercussions of this pandemic persisting to this day (2). SARS-CoV-2 primarily spreads through aerosols, targeting the respiratory system and resulting in symptoms that may progress to severe pneumonia or respiratory failure (3,4). Recent studies have indicated that the virus can lead to varying levels of lung damage and respiratory complications, potentially causing long-term health issues such as pulmonary fibrosis, pleural adhesions, weakened immune function, and chronic inflammation (5,6). Unfortunately, many patients may experience long-term pulmonary damage (7). As a result, individuals recovering from COVID-19 can be subject to increased surgical risks and difficulties when undergoing lung resection.

In general, lung surgery for patients with NSCLC recovering from COVID-19 is considered safe if performed in accordance with established guidelines (3,8,9). However, research indicates that these patients may experience longer surgical durations, more complications, and delayed recovery following surgery (10-14). These challenges are particularly problematic for older adult patients, who are more likely to experience long-term complications from COVID-19 and are at increased risk during lung surgery as compared to younger individuals (15,16). Consequently, older patients, particularly those of advanced age, are at a higher risk for severe postoperative complications and mortality following lung cancer surgery (17,18). Our recent findings confirmed that patients with NSCLC aged 65 years and older are more likely to develop postoperative complications that necessitate intervention (19). Therefore, assessing the impact of previous COVID-19 infection on the safety and feasibility of lung surgery and accurately predicting surgical challenges and risks are crucial for optimizing perioperative outcomes in older adult patients with NSCLC.

This study examined the influence of a past COVID-19 infection on surgical difficulty and risks, identified high-risk subgroups after COVID-19 infection, and developed prediction models using retrospective data from seven high-volume institutions, representing the most extensive cohort of older adult patients with NSCLC compiled to date. The results may provide valuable evidence for informing the development of personalized surgical and perioperative management strategies for older adult patients with NSCLC receiving curative surgery in the COVID-19 era. We present this article in accordance with the TRIPOD reporting checklist (available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2025-761/rc).

Methods

Study design

A retrospective review was conducted on patients with clinical T1-3N1-2M0 NSCLC aged 65 years or older who underwent curative lung surgery at seven high-volume tertiary medical centers in China between January 2021 and May 2024 (Figure 1). The participated centers are as follows: Shanghai Chest Hospital, Putuo District People’s Hospital, The Affiliated Lihuili Hospital of Ningbo University, The First Affiliated Hospital of Ningbo University, Shanghai Tongren Hospital, Wenzhou People’s Hospital, and The First Affiliated Hospital of Shaoyang University. The following exclusion criteria were applied: (I) lack of critical information; (II) exploratory or palliative operations; (III) bilateral surgery or simultaneous additional esophageal, mediastinal, or cardiac procedures; and (IV) a history of any malignancy. Disease staging was performed according to the eighth edition of the International Association for the Study of Lung Cancer (IASLC) TNM classification (20). The surgical difficulty was evaluated using the incidence of conversion, while the surgical risk was assessed using severe postoperative complications (21). This study was approved by the Institutional Review Board (IRB) of Shanghai Chest Hospital (approval No. IS24152; approval date: December 11, 2024) and all participating hospitals were informed and agreed with this study. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The requirement of informed consent from participants was waived by the IRB of Shanghai Chest Hospital due to the study’s retrospective design.

Figure 1 Flowchart of the study. BMI, body mass index; COVID-19, coronavirus disease 2019; DLCO, diffusing capacity for carbon monoxide; ECOG, Eastern Cooperative Oncology Group; FEV1, forced expiratory volume in 1 s; LN, lymph node; NSCLC, non-small cell lung cancer; NCOV, no history of COVID-19 infection; PCOV, history of COVID-19 infection; PSM, propensity-score matching.

To address missing data, we summarized the cases with incomplete information and attempted to retrieve the missing values by querying our electronic medical record systems. Ultimately, 425 out of 26,491 cases had missing data that could not be recovered for any of the variables required for analysis, and these cases were excluded from the study. Given the small number of excluded cases, we believe this approach is unlikely to have introduced significant bias or caused a substantial loss of statistical power.

Preoperative measurement and surgical techniques

The detailed methods used to preoperatively evaluate current and past COVID-19 infections, surgical tolerance, lymph node (LN) status, and distant metastasis are described in our previous publication (19). Patients with uncertain or unclear COVID-19 histories were categorized as having an unknown status and excluded from the study initially. The smoking history of patients was categorized by pack-years as follows: never smokers (0 pack-year), light smokers (>0 to <30 pack-years), and heavy smokers (≥30 pack-years) (22).

Curative surgery was performed with techniques outlined in previous studies (16,23).

Curative resection was defined as follows: (I) sub-lobectomy with a resection margin greater than the tumor’s size, along with selective mediastinal LN sampling for clinical IA disease, when the radiographic tumor size was ≤2 cm; and (II) lobectomy, bilobectomy, or pneumonectomy, accompanied by systematic mediastinal LN dissection. Surgery duration was measured from the first incision to the final closure. Conversion was defined as a procedure that began with MIS but concluded with a rib-spreading thoracotomy.

Postoperative management

Postoperative care followed an enhanced recovery protocol for all patients, which involved smoking cessation starting 2 weeks before surgery, the use of breathing exercises, and encouraging early physical activity after the procedure. Complications occurring within 90 days after surgery were categorized via the Clavien-Dindo classification system (24). Severe complications were defined as those rated grade III or higher on the Clavien-Dindo scale. Pulmonary complications following surgery were identified in accordance with the European Perioperative Clinical Outcome guidelines (25). The operational definitions were established as follows: (I) air leak: detected by the presence of bubbling in the closed chest drainage system during spontaneous breathing, deep inspiration, or coughing. A prolonged air leak was defined as one persisting beyond 5 days postoperatively. (II) Pleural effusion: diagnosed on chest radiography by features such as blunting of the costophrenic angle, obscuration of the ipsilateral hemidiaphragm in the upright position, displacement of adjacent anatomical structures, or a diffuse hazy opacity involving one hemithorax with preservation of vascular markings in the supine position. (III) Atelectasis: identified by pulmonary opacification accompanied by mediastinal, hilar, or diaphragmatic shift toward the affected side, together with compensatory hyperinflation of the surrounding non-atelectatic lung tissue.

Statistical analysis

Categorical data are presented as frequencies and percentages, while continuous variables are expressed as the median and interquartile range (IQR). The Pearson Chi-squared test or Fisher exact test was used for comparisons of categorical variables, and continuous variables were compared with either the Student t-test or the Mann-Whitney test depending on the data distribution. Univariable logistic regression was performed to screen the potential risk factors and followed by multivariable analysis coupled with a backward stepwise approach and the Wald test. Variables with a P value <0.05 from the univariable analysis were included in the multivariable model to identify predictors of MIS conversion and severe postoperative complications. Propensity-score matching (PSM) was applied with a 1:2 nearest-neighbor algorithm and a caliper width to facilitate a 1:1 comparison between a group with a history of COVID-19 (PCOV group) and the one without a history (NCOV group), with all patient baseline characteristics being considered. Standard mean differences (SMDs) were used to evaluate the balance of baseline covariates between matched groups, with an absolute SMD <0.10 indicating negligible differences.

Prediction models were constructed based on parameters identified as significant in the multivariable analysis, with the results displayed in a nomogram for a visual, point-based estimation of probabilities. The models’ performance was evaluated based on two main criteria: (I) discrimination, as assessed by the concordance index (C-index), which corresponds to the area under the receiver operating characteristic (ROC) curve (AUC); and (II) calibration, which was measured through calibration curves comparing predicted and observed outcomes. The AUC values ranged from 0.5 (random prediction) to 1.0 (perfect prediction), with higher values indicating better model accuracy. Generally, C-index and AUC values above 0.70 indicate good accuracy. Internal validation was performed through 1,000 bootstrapped resamples to reduce overfitting and assess optimism. Patients included in the PSM were designated as the training cohort, while those excluded from PSM were placed in external validation cohort 1 (Figure S1). Meanwhile, cases that were matched by PSM from NSCLC patients who underwent surgery between June 2024 and October 2024 at our centers were designed as the external validation cohort 2.

Statistical analyses and PSM were performed with SPSS version 26.0 (IBM Corporation, Armonk, NY, USA), and the nomogram was generated using R version 4.4.1 (The R Foundation for Statistical Computing) for Windows. A two-sided P value of <0.05 was considered statistically significant.

Results

Patient baseline characteristics

As outlined in Table 1, a total of 22,101 patients were included in the study. Among them, 12,998 had no prior history of COVID-19 (NCOV group), while 9,103 patients had a history of COVID-19 before surgery (PCOV group). Significant statistical differences were observed across the groups in 11 baseline characteristics. Subsequently, PSM was carried out, generating 7330 cases in which the patient characteristics were well-matched across both groups. Patient baseline characteristics of the external validation cohorts 1 and 2 are summarized in Table S1.

Perioperative outcomes and postoperative complications

There were 6,580 MIS cases and 750 open cases in the NCOV group, and 6,594 MIS cases and 736 open cases in the PCOV group. By comparison, the NCOV and PCOV groups exhibited a comparable MIS conversion rate (5.9% vs. 6.5%, P=0.17; Table 2) and causes for conversion (P=0.33; Table S2). However, as compared with the NCOV group, the PCOV group had a notably longer median surgical duration (NCOV: 89.0 min, IQR: 70.0–103.5 min; PCOV: 99.0 min, IQR: 85.5–111.0 min; P<0.001), median chest tube length (NCOV: 3 days, IQR: 3–4; PCOV: 4 days, IQR: 3–4 days; P<0.001), and postoperative hospitalization time (NCOV: 4 days, IQR: 3–5 days; PCOV: 5 days, IQR: 3–6 days; P<0.001).

Moreover, the PCOV group had a significantly higher incidence of postoperative complications than the NCOV group (20.2% vs. 18.7%; P=0.03; Table 3). However, the two cohorts had similar severe complication rates (Clavien-Dindo grade ≥III; 6.0% vs. 6.6%; P=0.13) and Clavien-Dindo grade distributions (P=0.16). Further comparison indicated that the PCOV group, as compared to the NCOV group, had an increased incidence of pulmonary complications, particularly atelectasis (9.6% vs. 8.5%; P=0.01) and prolonged air leak (3.7% vs. 3.0%, P=0.02).

Risk factors for increased surgical difficulty and risk in patients with a history of COVID-19

Further stratification analyses were performed to screen populations with higher surgical difficulty and risk after COVID-19 infection based on the incidence of MIS conversion and severe postoperative complications, respectively. Generally, heavy smokers were associated with a higher conversion rate following COVID-19 (11.5% vs. 8.6%; P=0.01; Table S3), with logistic regression analysis yielding an odds ratio (OR) of 1.283 [95% confidence interval (CI): 1.040–1.687; Figure 2]. Additionally, a heightened risk of developing severe comorbidities following COVID-19 was associated with an age ≥75 years (9.0% vs. 6.7%, P=0.04) and heaving smoking (10.8% vs. 8.5%, P=0.03) (Table S4), with logistic regression analysis yielding ORs of 1.312 (95% CI: 1.013–1.799) and 1.297 (95% CI: 1.022–1.639), respectively (Figure 2).

Figure 2 Stratified logistic regression analysis identifying whether past COVID-19 infection independently increased MIS conversion and incidence of severe postoperative complications (Clavien-Dindo grade ≥ III) risks. Within each stratified group, univariable logistic regression was used to assess the potential influence of COVID-19 history and to screen for risk factors. This was followed by multivariable logistic regression to control for confounding factors with P<0.05, specifically in stratified groups in which a COVID-19 history was identified as a potential risk factor. The OR [95% CI] values indicate the risks of PCOV vs. NCOV. ADC, adenocarcinoma; BMI, body mass index; CI, confidence interval; cLN, clinical lymph node; COVID-19, coronavirus disease 2019; cT, clinical T; DLCO, diffusing capacity for carbon monoxide; ECOG, Eastern Cooperative Oncology Group; FEV1, forced expiratory volume in 1 s; MIS, minimally invasive surgery; NCOV, no history of COVID-19 infection; OR, odds ratio; PCOV, history of COVID-19 infection.

The perioperative outcomes and detailed postoperative comorbidities were then analyzed for these high-risk patients, and it was found that those with previous COVID-19 infection, as compared with those without one, experienced longer operation times, chest tube durations, and postoperative hospital stays (Tables S5,S6), along with increased incidences of overall and pulmonary comorbidities (Tables S7,S8).

Development and external validation of novel models for preoperatively predicting surgical difficulty

Subsequently, novel prediction models based on patient clinical characteristics were developed to preoperatively forecast surgical difficulties. Initially, multivariable logistic regression identified six independent risk factors associated with MIS conversion in patients with a COVID-19 history, including smoking history, tumor histology, resection extent, clinical T stage, clinical LN metastasis, and neoadjuvant therapy (Table S9). These candidates were then used to develop a nomogram (Figure 3A), with internal validation producing an AUC value of 0.760, which was equivalent to the C-index (Figure 3B). The calibration curve demonstrated high consistency between the predicted and observed conversion probabilities (Figure 3C). Subsequent validation in two external cohorts yielded AUC values of 0.744 and 0.757 (Figure 3D,3E). Similarly, independent risk factors for conversion were identified in both the overall and non-COVID-19 cohorts (Tables S9,S10). Two additional nomograms were developed, which also demonstrated good discrimination and calibration (Figures S2,S3).

Figure 3 Establishment and validation of a prediction model for MIS conversion in patients with a COVID-19 history. (A) Nomogram of the prediction model. (B) ROC curve in the internal validation cohort. (C) Calibration curve of the prediction model. ROC curves in (D) external validation cohort 1 and (E) 2. ADC, adenocarcinoma; AUC, area under the curve; COVID-19, coronavirus disease 2019; LN, lymph node; MIS, minimally invasive surgery; ROC, receiver operating characteristic; T, tumor.

For heavy smokers with a previous COVID-19 infection, the population associated with increased surgical difficulty, the independent risk factors for MIS conversion were identified (Table S11). Six factors were used to create a nomogram, which demonstrated good performance and calibration (Figure S4A-S4E). These results indicated that the models could effectively predict conversion probability for older adult patients with NSCLC.

Development and external validation of novel models for preoperatively predicting surgical risks

Prediction models were also developed to forecast surgical risk. Multivariable logistic regression identified eight independent risk factors for severe postoperative complications in patients with a COVID-19 history (Table S12). A nomogram based on these factors achieved AUC and C-index values of 0.756 in internal validation, with the calibration curve demonstrating good discrimination (Figure 4A-4C). External validation of the model yielded AUC values of 0.745 (External Cohort 1; Figure 4D) and 0.753 (External Cohort 2; Figure 4E). Independent risk factors for severe complications were similarly examined in the overall and non-COVID-19 cohorts, with eight and seven factors being identified, respectively (Tables S12,S13). Two nomograms were then developed for each cohort and demonstrated good discrimination and calibration (Figures S5,S6).

Figure 4 Establishment and validation of a prediction model for severe postoperative complications (Clavien-Dindo grade ≥ III) in patients with a COVID-19 history. (A) Nomogram of the prediction model. (B) ROC curve in the internal validation cohort. (C) Calibration curve of the prediction model. ROC curves in (D) external validation cohort 1 and (E) 2. ADC, adenocarcinoma; AUC, area under the curve; COVID-19, coronavirus disease 2019; LN, lymph node; MIS, minimally invasive surgery; ROC, receiver operating characteristic; T, tumor.

Finally, six factors independent risk factors for severe complications were identified in patients aged ≥75 years and heavy smokers, respectively (Tables S14,S15). These factors were used to create prediction models with good performance and calibration (Figures S7,S8). The results suggested that the prediction models could effectively forecast the probability of severe complications in older adult patients with NSCLC.

Discussion

The COVID-19 pandemic has spread globally and may lead to long-term, highly variable respiratory, cardiac, immune, and coagulation-related complications, thereby potentially increasing surgical difficulty and risk (6,8,26-28). Unfortunately, these complications are particularly concerning for older adult patients, who are more vulnerable during lung surgery following COVID-19 than are younger individuals (15,16). Therefore, it is essential to assess the effect of prior COVID-19 infection on perioperative outcomes, screen those at higher surgical risk, and accurately predict the level of surgical difficulty to improve outcomes for older adult patients with NSCLC. In our study, we found that previous COVID-19 infection does not significantly increase the incidence of conversion or severe postoperative complications in these patients. However, heavy smokers and those aged ≥75 years may face heightened surgical challenges and risks following COVID-19. The developed models effectively predicted surgical difficulties and risks for older adult patients with NSCLC, both with and without a COVID-19 history, as well as those for high-risk populations. These findings may help inform patient-specific surgery and perioperative management strategies for older adult patients with NSCLC in the COVID-19 era.

Our findings further revealed that older adult patients with a history of COVID-19 underwent significantly longer surgical procedures, likely due to chest cavity fibrosis and the presence of adhesions caused by pneumonia and inflammatory pleural effusion induced by COVID-19 infection (5,6). Despite this, these complications did not substantially heighten surgical difficulty, as the incidence of MIS conversion was similar between the NCOV and PCOV groups. Given this, although this increase in operation duration may not significantly disrupt the surgical procedure, a longer operation time requires additional planning, particularly in terms of anesthesiology support and bed management. This consideration is especially important for high-volume centers to maintain efficiency and ensure optimal patient care during operations. Based on these results, we can conclude that curative surgery remains generally feasible for older adult patients with a history of COVID-19. Interestingly, we observed that heavy smokers had a higher incidence of conversion after COVID-19 infection. This could be explained by the fact that older adult heavy smokers with NSCLC are more prone to severe COVID-19, which often requires hospitalization or even intensive care, potentially resulting in significant chest cavity adhesions and fibrosis, thereby increasing the likelihood of conversion (15). Additional studies are required to further investigate the correlation between the severity of COVID-19 and surgical challenges in older adult patients with NSCLC.

Pulmonary operation is considered safe for patients with NSCLC recovering from COVID-19 and is associated with a low incidence of life-threatening complications and mortality (3). However, older adult patients often experience more enduring complications from COVID-19, have more comorbidities, and are more vulnerable during lung surgery than are younger individuals (15,16). Consequently, this population is considered at high risk for developing postoperative complications following lung cancer surgery (29,30). Our findings indicated that the PCOV and NCOV groups had comparable incidences of severe postoperative complications, with both groups exhibiting low mortality rates. Given this, curative operation could be considered feasible and safe for older adult patients with NSCLC. However, patients with a past COVID-19 infection had notably more pulmonary complications than did those without, likely due to lung damage and respiratory issues caused by past SARS-CoV-2 infection (31). Additionally, our findings indicated that those aged ≥75 years and heavy smokers were at a higher risk of developing severe complications after COVID-19 infection. This can be attributed to their vulnerability to the long-term pathological conditions caused by COVID-19, rendering them more susceptible to adverse conditions both during and after operations. These results emphasize the importance of a comprehensive presurgical assessment and more intensive postsurgical care for these high-risk populations, which may involve, but is not limited to, the following: (I) personalization of presurgical respiration exercises, postsurgical pain management, and expectoration techniques to maximize their effectiveness; (II) prolongation of the smoking cessation period beyond the standard 2 weeks before operation, with careful consideration of the potential for disease progression; and (III) prolongation of nebulized inhalation therapy both before and after surgery according to each patient’s respiratory function and smoking history. These individualized approaches could contribute to improving perioperative care and clinical outcomes for these high-risk groups.

In this study, distinct nomograms were developed for different patient subgroups, including the overall, PCOV, NCOV, very old (aged ≥75 years), and heavy smoking subcohorts, as these populations exhibited distinct risk factors for MIS conversion and severe postoperative complications. Therefore, the creation of separate nomograms for these distinct patient cohorts enables preoperative, patient-specific forecasting of surgical difficulty and risk, providing personalized information for perioperative management. Notably, the established models established in this study achieved an AUC value of approximately 0.74, which is slightly higher than that reported in previous studies predicting postoperative complications or perioperative outcomes for NSCLC patients (32-34). Therefore, we believe that our prediction models demonstrate reasonable forecasting efficacy for surgical difficulty and risk.

Two international cohort studies and accompanying guidelines recommend deferring elective surgery for at least 7 weeks following a COVID-19 diagnosis to reduce perioperative complications and mortality (30,35). However, these recommendations were largely based on studies conducted before the widespread rollout of COVID-19 vaccination, and therefore did not account for the protective effects of vaccination on postoperative outcomes. More recent evidence from China has suggested that delaying pulmonary tumor resection by at least 4 weeks after COVID-19 infection is sufficient to mitigate excess surgical risk (28,36). Among patients who met this threshold, a prior COVID-19 infection was no longer identified as an independent risk factor for adverse postoperative outcomes. In our study, conducted between 2021 and 2024, all surgeries were performed at least 4 weeks after SARS-CoV-2 infection, in accordance with established institutional protocols, as previously reported in our earlier publication. Therefore, despite not capturing the exact time interval from infection, we believe this limitation may have a minimal impact on the overall conclusions of our study.

To our knowledge, this study is the largest real-world analysis examining the influence of COVID-19 history on the perioperative outcomes in older adult patients with NSCLC, including 22,101 cases across seven medical centers in China. However, several limitations were present that should be acknowledged. First, although PSM was employed to balance the baseline clinical characteristics across the two cohorts, the retrospective nature of this study might have led to potential biases in patient inclusion. As such, prospective research is required to further confirm these results. Second, this study did not examine the effects of the operation timing after SARS-CoV-2 infection, the influence of different variants of the virus, or the severity of COVID-19 symptoms on perioperative outcomes. Therefore, further studies focusing on the impact of these factors on surgical difficulty and risk are necessary. Finally, although this study primarily focused on short-term postoperative outcomes, it did not assess long-term survival, highlighting the need for extended follow-up to determine whether a history of COVID-19 influences the prognoses of older adult patients.

Conclusions

Past COVID-19 infection did not significantly increase surgical difficulty or risk for older adult patients with NSCLC. However, heavy smokers were associated with greater surgical difficulty, and both individuals aged ≥75 years and heavy smokers with a history of COVID-19 infection were associated with heightened surgical risk. The surgical difficulty and risk of older adult patients with NSCLC with or without a COVID-19 history could be effectively predicted be the established models. These findings could offer valuable evidence for informing the establishment of tailored, patient-specific surgical and perioperative management approaches for older adult patients with NSCLC receiving curative surgery in the post–COVID-19 era.

Acknowledgments

The authors appreciate the great support from Dr. Toyofumi Fengshi Chen-Yoshikawa (Nagoya University Graduate School of Medicine, Japan) and Dr. Fumihiro Ishibashi (National Hospital Organization Chiba Medical Center, Japan) in improving the quality of this paper.

Footnote

Reporting Checklist: The authors have completed the TRIPOD reporting checklist. Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2025-761/rc

Data Sharing Statement: Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2025-761/dss

Peer Review File: Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2025-761/prf

Funding: This study was supported by Nature Science Foundation of China (No. 82473210), the Development Center for Medical Science & Technology National Health Commission of the People’s Republic of China (No. WA2021RW27), the Shanghai Charity Foundation (No. ZG2513), the Zhejiang Province Medical and Health Project (No. 2022KY296), the Clinical Scientific Research Program of Wu Jieping Medical Funding (No. 320.6750.2022-17-58), and the Natural Science Foundation of Ningbo (No. 2021J278).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2025-761/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The was approved by the Institutional Review Board (IRB) of Shanghai Chest Hospital (approval No. IS24152) and all participating hospitals were informed and agreed with this study. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The requirement of informed consent from participants was waived by the IRB of Shanghai Chest Hospital due to the study’s retrospective design.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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