scholarly journals Development and External Validation of a Nomogram for Predicting Overall Survival in Stomach Cancer: A Population-Based Study

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Haonan Ji ◽  
Huita Wu ◽  
Yu Du ◽  
Li Xiao ◽  
Yiqin Zhang ◽  
...  
Keyword(s):  
Overall Survival ◽  
Prognostic Factors ◽  
Stomach Cancer ◽  
External Validation ◽  
Model Development ◽  
Training Group ◽  
Population Based ◽  
Survival Prediction ◽  
Kolmogorov Smirnov ◽  
Testing Group

Objective. The study was to develop and externally validate a prognostic nomogram to effectively predict the overall survival of patients with stomach cancer. Methods. Demographic and clinical variables of patients with stomach cancer in the Surveillance, Epidemiology, and End Results (SEER) database from 2007–2016 were retrospectively collected. Patients were then divided into the Training Group (n = 4,456) for model development and the Testing Group (n = 4,541) for external validation. Univariate and multivariate Cox regressions were used to explore prognostic factors. The concordance index (C-index) and the Kolmogorov–Smirnov (KS) value were used to measure the discrimination, and the calibration curve was used to assess the calibration of the nomogram. Results. Prognostic factors including age, race, marital status, TNM stage, surgery, chemotherapy, grade, and the number of regional nodes positive were used to construct a nomogram. The C-index was 0.790 and the KS value was 0.45 for the Training Group, and the C-index was 0.789 for the Testing Group, all suggesting the good performance of the nomogram. Conclusion. We have developed an effective nomogram with ten easily acquired prognostic factors. The nomogram could accurately predict the overall survival of patients with stomach cancer and performed well on external validation, which would help improve the individualized survival prediction and decision-making, thereby improving the outcome and survival of stomach cancer.

A population-based validation of a clinical age-based prognostic tool to predict survival in melanoma patients (Preprint)

2021 ◽  
Author(s):  
Yu-Jen Wang ◽  
Mingchih Chen ◽  
Yen Chun Huang ◽  
Tian-Shyug Lee
Keyword(s):  
Machine Learning ◽  
Overall Survival ◽  
Prognostic Factors ◽  
Outcome Prediction ◽  
Prediction Models ◽  
Population Based ◽  
Survival Prediction ◽  
Prediction Tool ◽  
Old Patients ◽  
Melanoma Patients

BACKGROUND Melanoma is the most serious form of skin cancer, and the treatment can be challenging if the disease progresses to the metastatic stage. Depth of invasion is a good prognostic factor for predicting outcome. However, no good outcome prediction system that combines the staging system with other chronic systemic diseases is available to date. We investigated melanoma-related data from a population-based database and developed an outcome prediction tool for melanoma patients via machine learning. OBJECTIVE Build up a prediction tool for melanoma patients METHODS The clinical data of patients with melanoma were extracted from Taiwan’s National Health Insurance Research Database between 2008 and 2015 and were analysed in this study. Clinical data including demographic, pathologic, staging, and treatment data from melanoma patients over 18 years old were abstracted and collected. Prognostic factors were analyzed. Logistic regression (LR), random forest (RF) modelling, and multivariate adaptive regression splines (MARS) were applied to calculate predicted overall survival (OS). A 5-fold cross-validation method was applied. Two age groups (≥64 years old as the older age group and <64 years old as the general population group) with different prognostic factors were identified, and prognostic models for survival outcomes were built. RESULTS A total of 3481 patients were enrolled in our study. The 1-, 3-, and 5-year overall survival rates were 92.2%, 80.1%, and 70.3%, respectively. The Cox proportional hazard model showed that older age, male sex, higher grade, higher clinical stage, larger tumour size, positive surgical margins, no surgical intervention, and a higher Charlson comorbidity index (CCI) were associated with higher hazard ratios. LR, RF, and MARS techniques were used to validate the overall survival without tracking time, the accuracy of the MARS model for the <64-year-old patients and ≥64-year-old patients was 90.4% and 80.7%, respectively, with 3-, and 5-year the accuracy of prediction models are 94% and 89.6%. CONCLUSIONS Machine learning techniques offer excellent survival prediction in melanoma patients. Age-based survival prediction models may be applied for better clinical decision making. CLINICALTRIAL N/A

scholarly journals Comparing the characteristics and predicting the survival of patients with head and neck melanoma versus body melanoma: a population-based study

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Yuxin Ding ◽  
Runyi Jiang ◽  
Yuhong Chen ◽  
Jing Jing ◽  
Xiaoshuang Yang ◽  
...  
Keyword(s):  
Head And Neck ◽  
Health Management ◽  
External Validation ◽  
Area Under The Curve ◽  
Population Based ◽  
Survival Prediction ◽  
Cancer Specific Survival ◽  
Cox Models ◽  
Lentigo Maligna Melanoma ◽  
Clinical Tools

Abstract Background Previous studies reported cutaneous melanoma in head and neck (HNM) differed from those in other regions (body melanoma, BM). Individualized tools to predict the survival of patients with HNM or BM remain insufficient. We aimed at comparing the characteristics of HNM and BM, developing and validating nomograms for predicting the survival of patients with HNM or BM. Methods The information of patients with HNM or BM from 2004 to 2015 was obtained from the Surveillance, Epidemiology, and End Results (SEER) database. The HNM group and BM group were randomly divided into training and validation cohorts. We used the Kaplan-Meier method and multivariate Cox models to identify independent prognostic factors. Nomograms were developed via the rms and dynnom packages, and were measured by the concordance index (C-index), the area under the curve (AUC) of the receiver operating characteristic (ROC) curve and calibration plots. Results Of 70,605 patients acquired, 21% had HNM and 79% had BM. The HNM group contained more older patients, male sex and lentigo maligna melanoma, and more frequently had thicker tumors and metastases than the BM group. The 5-year cancer-specific survival (CSS) and overall survival (OS) rates were 88.1 ± 0.3% and 74.4 ± 0.4% in the HNM group and 92.5 ± 0.1% and 85.8 ± 0.2% in the BM group, respectively. Eight variables (age, sex, histology, thickness, ulceration, stage, metastases, and surgery) were identified to construct nomograms of CSS and OS for patients with HNM or BM. Additionally, four dynamic nomograms were available on web. The internal and external validation of each nomogram showed high C-index values (0.785–0.896) and AUC values (0.81–0.925), and the calibration plots showed great consistency. Conclusions The characteristics of HNM and BM are heterogeneous. We constructed and validated four nomograms for predicting the 3-, 5- and 10-year CSS and OS probabilities of patients with HNM or BM. These nomograms can serve as practical clinical tools for survival prediction and individual health management.

Demographic, Clinical, and Prognostic Factors of Ovarian Clear Cell Adenocarcinomas According to Endometriosis Status

2017 ◽  
Vol 27 (9) ◽  
pp. 1804-1812 ◽  
Author(s):  
Tine H. Schnack ◽  
Estrid Høgdall ◽  
Lotte Nedergaard Thomsen ◽  
Claus Høgdall
Keyword(s):  
Overall Survival ◽  
Prognostic Factors ◽  
Cox Regression ◽  
Clear Cell ◽  
Statistical Tests ◽  
Gynecological Cancer ◽  
Population Based ◽  
Clear Cell Adenocarcinoma ◽  
Ovarian Endometriosis ◽  
Increased Risk

ObjectivesWomen with endometriosis carry an increased risk for ovarian clear cell adenocarcinomas (CCCs). Clear cell adenocarcinoma may develop from endometriosis lesions. Few studies have compared clinical and prognostic factors and overall survival in patients diagnosed as having CCC according to endometriosis status.MethodsPopulation-based prospectively collected data on CCC with coexisting pelvic (including ovarian; n = 80) and ovarian (n = 46) endometriosis or without endometriosis (n = 95) were obtained through the Danish Gynecological Cancer Database. χ2 Test, independent-samples t test, logistic regression, Kaplan-Meier test, and Cox regression were used. Statistical tests were 2 sided. P values less than 0.05 were considered statistically significant.ResultsPatients with CCC and pelvic or ovarian endometriosis were significantly younger than CCC patients without endometriosis, and a higher proportion of them were nulliparous (28% and 31% vs 17% (P = 0.07 and P = 0.09). Accordingly, a significantly higher proportion of women without endometriosis had given birth to more than 1 child. Interestingly, a significantly higher proportion of patients with ovarian endometriosis had pure CCCs (97.8% vs 82.1%; P = 0.001) as compared with patients without endometriosis. Overall survival was poorer among CCC patients with concomitant ovarian endometriosis (hazard ratio, 2.56 [95% confidence interval, 1.29–5.02], in the multivariate analysis.ConclusionsAge at CCC diagnosis and parity as well as histology differ between CCC patients with and without concomitant endometriosis. Furthermore, CCC patients with concomitant ovarian endometriosis have a poorer prognosis compared with endometriosis-negative CCC patients. These differences warrant further research to determine whether CCCs with and without concomitant endometriosis develop through distinct pathogenic pathways.

scholarly journals A Novel Nomogram for Predicting Cancer-Specific Survival in Patients With Spinal Chordoma: A Population-Based Analysis

2021 ◽  
Vol 20 ◽  
pp. 153303382110365
Author(s):  
Zhangheng Huang ◽  
Zhiyi Fan ◽  
Chengliang Zhao ◽  
He Sun
Keyword(s):  
Prognostic Factors ◽  
Area Under The Curve ◽  
Risk Groups ◽  
Population Based ◽  
Disease Stage ◽  
Survival Prediction ◽  
Cancer Specific Survival ◽  
Spinal Chordoma ◽  
Prediction Of Prognosis ◽  
High Degree

Background: Chordoma is a rare malignant bone tumor, and the survival prediction for patients with chordoma is difficult. The objective of this study was to construct and validate a nomogram for predicting cancer-specific survival (CSS) in patients with spinal chordoma. Methods: A total of 316 patients with spinal chordoma were identified from the SEER database between 1998 and 2015. The independent prognostic factors for patients with spinal chordoma were determined by univariate and multivariate Cox analyses. The prognostic nomogram was established for patients with spinal chordoma based on independent prognostic factors. Furthermore, we performed internal and external validations for this nomogram. Results: Primary site, disease stage, histological type, surgery, and age were identified as independent prognostic factors for patients with spinal chordoma. A nomogram for predicting CSS in patients with spinal chordoma was constructed based on the above 5 variables. In the training cohort, the area under the curve for predicting 1-, 3-, and 5-year CSS were 0.821, 0.856, and 0.920, respectively. The corresponding area under the curve in the validation cohort were 0.728, 0.804, and 0.839, respectively. The calibration curves of the nomogram showed a high degree of agreement between the predicted and the actual results, and the decision curve analysis further demonstrated the satisfactory clinical utility of the nomogram. Conclusions: The prognostic nomogram provides a considerably more accurate prediction of prognosis for patients with spinal chordoma. Clinicians can use it to categorize patients into different risk groups and make personalized treatment methods.

scholarly journals Breast Subtypes and Prognosis of Breast Cancer Patients With Initial Bone Metastasis: A Population-Based Study

2020 ◽  
Vol 10 ◽  
Author(s):  
Deyue Liu ◽  
Jiayi Wu ◽  
Caijin Lin ◽  
Lisa Andriani ◽  
Shuning Ding ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Overall Survival ◽  
Prognostic Factors ◽  
Metastatic Breast Cancer ◽  
Bone Metastasis ◽  
Cancer Patients ◽  
Metastatic Breast ◽  
Risk Groups ◽  
Population Based ◽  
Breast Cancer Patients

BackgroundMetastatic breast cancer (MBC) is a highly heterogeneous disease and bone is one of the most common metastatic sites. This retrospective study was conducted to investigate the clinical features, prognostic factors and benefits of surgery of breast cancer patients with initial bone metastases.MethodsFrom 2010 to 2015, 6,860 breast cancer patients diagnosed with initial bone metastasis were analyzed from Surveillance, Epidemiology, and End Results (SEER) database. Univariate and Multivariable analysis were used to identify prognostic factors. A nomogram was performed based on the factors selected from cox regression result. Survival curves were plotted according to different subtypes, metastatic burdens and risk groups differentiated by nomogram.ResultsHormone receptor (HR) positive/human epidermal growth factor receptor 2 (HER2) positive patients showed the best outcome compared to other subtypes. Patients of younger age (&lt;60 years old), white race, lower grade, lower T stage (&lt;=T2), not combining visceral metastasis tended to have better outcome. About 37% (2,249) patients received surgery of primary tumor. Patients of all subtypes could benefit from surgery. Patients of bone-only metastases (BOM), bone and liver metastases, bone and lung metastases also showed superior survival time if surgery was performed. However, patients of bone and brain metastasis could not benefit from surgery (p = 0.05). The C-index of nomogram was 0.66. Cutoff values of nomogram point were identified as 87 and 157 points, which divided all patients into low-, intermediate- and high-risk groups. Patients of all groups showed better overall survival when receiving surgery.ConclusionOur study has provided population-based prognostic analysis in patients with initial bone metastatic breast cancer and constructed a predicting nomogram with good accuracy. The finding of potential benefit of surgery to overall survival will cast some lights on the treatment tactics of this group of patients.

scholarly journals Nomogram for predicting the overall survival and cancer-specific survival of patients with extremity liposarcoma: a population-based study

BMC Cancer ◽  
2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Lin Ye ◽  
Chuan Hu ◽  
Cailin Wang ◽  
Weiyang Yu ◽  
Feijun Liu ◽  
...  
Keyword(s):  
Overall Survival ◽  
Prognostic Factors ◽  
Area Under The Curve ◽  
Risk Groups ◽  
Population Based ◽  
Cancer Specific Survival ◽  
Kaplan Meier ◽  
Extremity Soft Tissue Sarcoma ◽  
Individual Survival ◽  
Size Grade

Abstract Background Extremity liposarcoma represents 25% of extremity soft tissue sarcoma and has a better prognosis than liposarcoma occurring in other anatomic sites. The purpose of this study was to develop two nomograms for predicting the overall survival (OS) and cancer-specific survival (CSS) of patients with extremity liposarcoma. Methods A total of 2170 patients diagnosed with primary extremity liposarcoma between 2004 and 2015 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate Cox analyses were performed to explore the independent prognostic factors and establish two nomograms. The area under the curve (AUC), C-index, calibration curve, decision curve analysis (DCA), Kaplan-Meier analysis, and subgroup analyses were used to evaluate the nomograms. Results Six variables were identified as independent prognostic factors for both OS and CSS. In the training cohort, the AUCs of the OS nomogram were 0.842, 0.841, and 0.823 for predicting 3-, 5-, and 8-year OS, respectively, while the AUCs of the CSS nomogram were 0.889, 0.884, and 0.859 for predicting 3-, 5-, and 8-year CSS, respectively. Calibration plots and DCA revealed that the nomogram had a satisfactory ability to predict OS and CSS. The above results were also observed in the validation cohort. In addition, the C-indices of both nomograms were significantly higher than those of all independent prognostic factors in both the training and validation cohorts. Stratification of the patients into high- and low-risk groups highlighted the differences in prognosis between the two groups in the training and validation cohorts. Conclusion Age, sex, tumor size, grade, M stage, and surgery status were confirmed as independent prognostic variables for both OS and CSS in extremity liposarcoma patients. Two nomograms based on the above variables were established to provide more accurate individual survival predictions for extremity liposarcoma patients and to help physicians make appropriate clinical decisions.

scholarly journals Time Trends and Prognostic Factors for Overall Survival in Myxoid Liposarcomas: A Population-Based Study

Sarcoma ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Jules Lansu ◽  
Winan J. Van Houdt ◽  
Michael Schaapveld ◽  
Iris Walraven ◽  
Michiel A. J. Van de Sande ◽  
...  
Keyword(s):  
Overall Survival ◽  
Prognostic Factors ◽  
The Netherlands ◽  
Metastatic Disease ◽  
Lower Limb ◽  
Tumor Size ◽  
Tumor Location ◽  
Population Based ◽  
Population Based Study ◽  
Over Time

Background. The purpose of this study was to evaluate the overall survival (OS) and associated characteristics for patients with Myxoid Liposarcoma (MLS) over time in The Netherlands. Methods. A population-based study was performed of patients with primary localized (n = 851) and metastatic (n = 50) MLS diagnosed in The Netherlands between 1989 and 2016, based on data from the National Cancer Registry. Results. The median age of the MLS patients was 49 years, and approximately two-thirds was located in the lower limb. An association was revealed between age and the risk of having a Round Cell (RC) tumor. OS rates for primary localized MLS were 93%, 83%, 78%, and 66% after 1, 3, 5, and 10 years, respectively. The median OS for patients with metastatic disease at diagnosis was 10 months. Increasing age (Hazard Ratio (HR) 1.05, p=0.00), a tumor size >5 cm (HR 2.18; p=0.00), and tumor location (trunk HR 1.29; p=0.09, upper limb HR 0.83; p=0.55, and “other” locations HR 2.73; p=0.00, as compared to lower limb) were independent prognostic factors for OS. The percentage of patients treated with radiotherapy (RT) increased over time, and preoperative RT gradually replaced postoperative RT. In contrast to patients with localized disease, significant improvement of OS was observed in patients with metastatic disease over time. Conclusions. In this large nationwide cohort, tumor size and tumor location were independent prognostic factors for OS. Furthermore, a higher probability of an RC tumor with increasing age was suggested. An increased use of RT over the years did not translate into improved OS for localized MLS.

scholarly journals Prognostic Factors and a Nomogram Predicting Overall Survival in Patients with Limb Chondrosarcomas: A Population-Based Study

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Xinjie Wu ◽  
Yanlei Wang ◽  
Wei Sun ◽  
Mingsheng Tan
Keyword(s):  
Overall Survival ◽  
Prognostic Factors ◽  
Clinical Decision Making ◽  
Proportional Hazards ◽  
Cox Regression ◽  
Training Group ◽  
Clinical Decision ◽  
The United States ◽  
Cox Proportional Hazards ◽  
Predictive Values

Introduction. We aimed to develop and validate a nomogram for predicting the overall survival of patients with limb chondrosarcomas. Methods. The Surveillance, Epidemiology, and End Results (SEER) program database was used to identify patients diagnosed with chondrosarcomas, from which data was extracted from 18 registries in the United States between 1973 and 2016. A total of 813 patients were selected from the database. Univariate and multivariate analyses were performed using Cox proportional hazards regression models on the training group to identify independent prognostic factors and construct a nomogram to predict the 3- and 5-year survival probability of patients with limb chondrosarcomas. The predictive values were compared using concordance indexes ( C -indexes) and calibration plots. Results. All 813 patients were randomly divided into a training group ( n = 572 ) and a validation group ( n = 241 ). After univariate and multivariate Cox regression, a nomogram was constructed based on a new model containing the predictive variables of age, site, grade, tumor size, histology, stage, and use of surgery, radiotherapy, or chemotherapy. The prediction model provided excellent C -indexes (0.86 and 0.77 in the training and validation groups, respectively). The good discrimination and calibration of the nomograms were demonstrated for both the training and validation groups. Conclusions. The nomograms precisely and individually predict the overall survival of patients with limb chondrosarcomas and could assist personalized prognostic evaluation and individualized clinical decision-making.

scholarly journals Characteristics and prognostic factors of age-stratified high-grade intracranial glioma patients: A population-based analysis

2019 ◽  
Author(s):  
Yun Sun ◽  
Zhi-yong Xiong ◽  
Peng-fei Yan ◽  
Liang-lei Jiang ◽  
Chuan-sheng Nie ◽  
...  
Keyword(s):  
Overall Survival ◽  
Prognostic Factors ◽  
Survival Data ◽  
Age Groups ◽  
High Grade Glioma ◽  
Population Based ◽  
High Grade ◽  
Treatment Protocols ◽  
Cox Models ◽  
Cause Specific Survival

We evaluated characteristics and different prognostic factors for survival in age-stratified high-grade glioma in a US cohort. Eligible patients were identified in the Surveillance, Epidemiology, and End Results (SEER) registries and stratified into 3 age groups: 20-39 years old (1,043 patients), 40-59 years old (4,503 patients), and >60 years old (5,045 patients). Overall and cancer-related survival data were obtained. Cox models were built to analyze the outcomes and risk factors. It showed that race was a prognostic factor for survival in patients 40 to 59 years old and in patients ≥60 years old. Partial resection was associated with lower overall survival and cause-specific survival in all age groups (overall survival: 20-39 yr: HR=6.41; 40-59 yr: HR=4.84; >60 yr: HR=5.06; cause-specific survival: 20-39 yr: HR=5.87; 40-59 yr: HR=4.01; >60 yr: HR=3.36). The study highlights that, while some prognostic factors are universal, others are age-dependent. The effectiveness of treatment approaches differs for patients in different age groups. Results of this study may help to develop personalized treatment protocols for glioma patients of different ages.

scholarly journals R-CHOEP-14 Is Associated with Superior Overall Survival Compared to R-CHOP-21 and R-CHOP-14 in Patients with DLBCL ≤70 Years – a Swedish Lymphoma Registry Population Based Study

Blood ◽  
2014 ◽  
Vol 124 (21) ◽  
pp. 4427-4427
Author(s):  
Tove Wästerlid ◽  
Erzsebet Szekely ◽  
Linda Werner Hartman ◽  
Mats Jerkeman
Keyword(s):  
Overall Survival ◽  
Prognostic Factors ◽  
Standard Treatment ◽  
Performance Status ◽  
Population Based ◽  
Disease Stage ◽  
Randomised Trials ◽  
Bulky Disease ◽  
Significant Difference ◽  
Intensive Regimen

Abstract Background: The current standard treatment for patients with diffuse large B-cell lymphoma (DLBCL) is Rituximab - Cyclophosphamide, Doxorubicin, Vincristine, Prednisone (R-CHOP). Two large randomised trials have been unable to establish a significant difference in outcome between patients receiving R-CHOP at 21 versus 14 day intervals regardless of age (Cunningham et al Lancet 2013, Delarue et al Lancet 2013). Another means of intensifying R-CHOP is by the addition of etoposide (R-CHOEP-14). As of yet, no randomised study in the rituximab era has been performed specifically evaluating the addition of etoposide. The aim of this study was to compare the chemotherapy regimens used to treat DLBCL in Sweden (R-CHOP-21, R-CHOP-14, R-CHOEP-14) among patients aged ≤70 in terms of overall survival, adjusted for clinical prognostic factors. Methods: The study population was identified through the Swedish Lymphoma Registry (SLR) 2007-2012. Data was analysed using STATA and SPSS. Age was modelled as splines in the multivariable analysis. Results: A total of 1745 patients aged ≤70 were identified in the SLR during the time-frame of this study. Median age was 61 years (range 18-70). Of these, 1331 had received R-CHOP-21 (n=302), R-CHOP-14 (n=872) or R-CHOEP-14 (n=157) and were included in the study. Median follow-up time for surviving patients was 49 months. Three-year overall survival rates were 86.7%, 79.6% and 87.5% for the patients who received R-CHOP-21, R-CHOP-14 and R-CHOEP-14 respectively. There was a significant disparity in the distribution of prognostic factors among patients receiving the various chemotherapy regimens with a lower proportion of patients with elevated serum lactate dehydrogenase (S-LDH), performance status >1, stage III-IV and presence of bulky disease (>10 cm) in the R-CHOP-21 group compared to the other regimens. As expected, the most intensive regimen, R-CHOEP-14 was more frequently given to younger patients (median age 49) with high-risk prognostic features. When adjusting for significant prognostic factors (age, performance status, S-LDH, bulky disease, stage and gender) in a multivariable Cox regression model, R-CHOEP-14 was found to be significantly superior both to R-CHOP-21 (Hazard Ratio (HR): 0.53, Confidence Interval (CI):0.3-0.9, p=0.026) and R-CHOP-14 (HR:0.63, CI:0.4-1.0, p=0.048). No significant difference between R-CHOP-14 and R-CHOP-21 was found (HR: 0.84, CI: 0.6-1.2, p=0.3), consistent with findings from randomised trials performed. Conclusion: In this population based series of DLBCL, the more intensive regimen R-CHOEP-14 was associated with superior overall survival in patients aged up to 70 years, indicating that this may be considered among the standard treatment options for this patient population. R-CHOEP-14 should preferably be compared to R-CHOP-21 in a randomised setting in order to further elucidate which patient groups that benefit the most from treatment intensification. Disclosures No relevant conflicts of interest to declare.

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