Cary Oberije - Profile on Academia.edu (original) (raw)
Papers by Cary Oberije
Implications of Clinicians' Attitudes Towards Clinical Decision Support Systems
Studies in health technology and informatics, 2020
Proceeding of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD 08, 2008
Privacy-preserving data mining (PPDM) is an emergent research area that addresses the incorporati... more Privacy-preserving data mining (PPDM) is an emergent research area that addresses the incorporation of privacy preserving concerns to data mining techniques. In this paper we propose a privacy-preserving (PP) Cox model for survival analysis, and consider a real clinical setting where the data is horizontally distributed among different institutions. The proposed model is based on linearly projecting the data to a lower dimensional space through an optimal mapping obtained by solving a linear programming problem. Our approach differs from the commonly used random projection approach since it instead finds a projection that is optimal at preserving the properties of the data that are important for the specific problem at hand. Since our proposed approach produces an sparse mapping, it also generates a PP mapping that not only projects the data to a lower dimensional space but it also depends on a smaller subset of the original features (it provides explicit feature selection). Real data from several European healthcare institutions are used to test our model for survival prediction of non-small-cell lung cancer patients. These results are also confirmed using publicly available benchmark datasets. Our experimental results show that we are able to achieve a near-optimal performance without directly sharing the data across different data sources. This model makes it possible to conduct large-scale multi-centric survival analysis without violating privacy-preserving requirements.
Data from: Prognostic value of blood-biomarkers related to hypoxia, inflammation, immune response and tumour load in non-small cell lung cancer – a survival model with external validation
![Research paper thumbnail of Erratum: “Machine learning algorithms for outcome prediction in (chemo)radiotherapy: An empirical comparison of classifiers” [Med. Phys. 45 (7), 3449-3459 (2018)]](https://attachments.academia-assets.com/83461870/thumbnails/1.jpg)
](
Purpose/Objective(s): Pneumonitis is one of the major treatment related toxicities from radiother... more Purpose/Objective(s): Pneumonitis is one of the major treatment related toxicities from radiotherapy for thoracic malignancies. Predictive factors for treatment related pneumonitis (TRP) are still controversial. The purpose of this study is to investigate whether the number of radiation treatment fields per fraction affects TRP among patients with non-small-cell lung cancer (NSCLC) receiving concurrent chemotherapy and 3-dimensional conformal radiation therapy (3D CRT). Materials/Methods: We determined the number of radiation treatment fields per fraction in 223 NSCLC patients who received definitive concurrent chemoradiation at our institution between 1998 and 2003. 3D CRT techniques were used in all patients. Clinical and dosimetric data of the patients were collected with the TRP graded using the NCI-CTC 3.0 criteria. Patients were categorized into 4 groups according to the number of fields per fraction: 2 fields, 3 fields, 4 fields and 5 fields or more. Patients with 2 fields per fraction were usually started with AP/PA followed by oblique beams. Dose-volume parameters for the normal lung including mean lung dose and volume of lung receiving above certain dose in each group of the patients were computed and compared using Kruskal-Wallis test. The actuarial incidence of TRP was calculated as the freedom from TRP within 18 months post-therapy. The risk of TRP was analyzed to evaluate the influence of the treatment fields per day using the log rank test. The mean lung doses were 22.0 ϩ/-6.4 Gy, 23.8 ϩ/-5.1 Gy, 21.6 ϩ/-5.5 Gy and 21.9 ϩ/-3.8 Gy for patients receiving 2,3,4 and 5 or more fields per fraction, respectively. There were no significant differences in the mean lung doses (pϭ0.115) or the distributions of the lung dose volume histograms among the four groups. In addition, the number of treatment fields irradiated per fraction had no significant influence on the freedom from TRP (p ϭ 0.738). We found no evidence that the number of radiation treatment fields per fractions affects the rate of TRP in NSCLC patients who received definitive concurrent chemoradiation. Further study is planned to identify any association between TRP and daily biological equivalent dose and irradiated volume of the lung, and to distinguish the severity of pulmonary injury caused by either low-dose high-volume versus high-dose low-volume treatments.
Radiotherapy and Oncology, 2010
Evidence is accumulating that radiotherapy of non-small cell lung cancer patients can be optimize... more Evidence is accumulating that radiotherapy of non-small cell lung cancer patients can be optimized by escalating the tumour dose until the normal tissue tolerances are met. To further improve the therapeutic ratio between tumour control probability and the risk of normal tissue complications, we firstly need to exploit inter patient variation. This variation arises, e.g. from differences in tumour shape and size, lung function and genetic factors. Secondly improvement is achieved by taking into account intra-tumour and intra-organ heterogeneity derived from molecular and functional imaging. Additional radiation dose must be delivered to those parts of the tumour that need it the most, e.g. because of increased radio-resistance or reduced therapeutic drug uptake, and away from regions inside the lung that are most prone to complication. As the delivery of these treatments plans is very sensitive for geometrical uncertainties, probabilistic treatment planning is needed to generate robust treatment plans. The administration of these complicated dose distributions requires a quality assurance procedure that can evaluate the treatment delivery and, if necessary, adapt the treatment plan during radiotherapy.
Radiotherapy and Oncology, 2009
Purpose: Extensive research has led to the identification of numerous dosimetric parameters as we... more Purpose: Extensive research has led to the identification of numerous dosimetric parameters as well as patient characteristics, associated with lung toxicity, but their clinical usefulness remains largely unknown. We investigated the predictive value of patient characteristics in combination with established dosimetric parameters. Patients and methods: Data from 438 lung cancer patients treated with (chemo)radiation were used. Lung toxicity was scored using the Common Toxicity Criteria version 3.0. A multivariate model as well as two single parameter models, including either V 20 or MLD, was built. Performance of the models was expressed as the AUC (Area Under the Curve). Results: The mean MLD was 13.5 Gy (SD 4.5 Gy), while the mean V 20 was 21.0% (SD 7.3%). Univariate models with V 20 or MLD both yielded an AUC of 0.47. The final multivariate model, which included WHO-performance status, smoking status, forced expiratory volume (FEV 1 ), age and MLD, yielded an AUC of 0.62 (95% CI: 0.55-0.69). Conclusions: Within the range of radiation doses used in our clinic, dosimetric parameters play a less important role than patient characteristics for the prediction of lung toxicity. Future research should focus more on patient-related factors, as opposed to dosimetric parameters, in order to identify patients at high risk for developing radiation-induced lung toxicity more accurately.
Tumor Volume Combined With Number of Positive Lymph Node Stations Is a More Important Prognostic Factor Than TNM Stage for Survival of Non–Small-Cell Lung Cancer Patients Treated With (Chemo)radiotherapy
International Journal of Radiation Oncology*Biology*Physics, 2008
The current tumor, node, metastasis system needs refinement to improve its ability to predict sur... more The current tumor, node, metastasis system needs refinement to improve its ability to predict survival of patients with non-small-cell lung cancer (NSCLC) treated with (chemo)radiation. In this study, we investigated the prognostic value of tumor volume and N status, assessed by using fluorodeoxyglucose-positron emission tomography (PET). Clinical data from 270 consecutive patients with inoperable NSCLC Stages I-IIIB treated radically with (chemo)radiation were collected retrospectively. Diagnostic imaging was performed using either integrated PET-computed tomography or computed tomography and PET separately. The Kaplan-Meier method, as well as Cox regression, was used to analyze data. Univariate survival analysis showed that number of positive lymph node stations (PLNSs), as well as N stage on PET, was associated significantly with survival. The final multivariate Cox model consisted of number of PLNSs, gross tumor volume (i.e., volume of the primary tumor plus lymph nodes), sex, World Health Organization performance status, and equivalent radiation dose corrected for time; N stage was no longer significant. Number of PLNSs, assessed by means of fluorodeoxyglucose-PET, was a significant factor for survival of patients with inoperable NSCLC treated with (chemo)radiation. Risk stratification for this group of patients should be based on gross tumor volume, number of PLNSs, sex, World Health Organization performance status, and equivalent radiation dose corrected for time.
European Journal of Cancer, 2007
Modelling antecedents of blood donation motivation among non-donors of varying age and education
British Journal of Psychology, 2009
Understanding blood donation motivation among non-donors is prerequisite to effective recruitment... more Understanding blood donation motivation among non-donors is prerequisite to effective recruitment. Two studies explored the psychological antecedents of blood donation motivation and the generalisability of a model of donation motivation across groups differing in age and educational level. An older well-educated population and a younger less well-educated population were sampled. The studies assessed the role of altruism, fear of blood/needles and donation-specific cognitions including attitudes and normative beliefs derived from an extended theory of planned behaviour (TPB). Across both samples, results showed that affective attitude, subjective norm, descriptive norm, and moral norm were the most important correlates of blood donation intentions. Self-efficacy was more important among the younger less well-educated group. Altruism was related to donation motivation but only indirectly through moral norm. Similarly, fear of blood/needles only had an indirect effect on motivation through affective attitude and self-efficacy. Additional analyses with the combined data set found no age or education moderation effects, suggesting that this core model of donation-specific cognitions can be used to inform future practical interventions recruiting new blood donors in the general population.
In this paper, we show that classical survival analysis involving censored data can naturally be ... more In this paper, we show that classical survival analysis involving censored data can naturally be cast as a ranking problem. The concordance index (CI), which quantifies the quality of rankings, is the standard performance measure for model assessment in survival analysis. In contrast, the standard approach to learning the popular proportional hazard (PH) model is based on Cox's partial likelihood. We devise two bounds on CI-one of which emerges directly from the properties of PH models-and optimize them directly. Our experimental results suggest that all three methods perform about equally well, with our new approach giving slightly better results. We also explain why a method designed to maximize the Cox's partial likelihood also ends up (approximately) maximizing the CI.
Acta Oncologica, 2010
Purpose . Metabolic response assessment is often used as a surrogate of local failure and surviva... more Purpose . Metabolic response assessment is often used as a surrogate of local failure and survival. Early identifi cation of patients with residual metabolic activity is essential as this enables selection of patients who could potentially benefi t from additional therapy. We report on the development of a pre-treatment prediction model for metabolic response using patient, tumor and treatment factors. Methods . One hundred and one patients with inoperable NSCLC (stage I-IV), treated with 3D conformal radical (chemo)-radiotherapy were retrospectively included in this study. All patients received a pre and post-radiotherapy fl uorodeoxyglucose positron emission tomography-computed tomography FDG-PET-CT scan. The electronic medical record system and the medical patient charts were reviewed to obtain demographic, clinical, tumor and treatment data. Primary outcome measure was examined using a metabolic response assessment on a postradiotherapy FDG-PET-CT scan. Radiotherapy was delivered in fractions of 1.8 Gy, twice a day, with a median prescribed dose of 60 Gy. Results . Overall survival was worse in patients with residual metabolic active areas compared with the patients with a complete metabolic response (p ϭ 0.0001). In univariate analysis, three variables were signifi cantly associated with residual disease: larger primary gross tumor volume (GTV primary , p ϭ 0.002), higher pre-treatment maximum standardized uptake value (SUV max , p ϭ 0.0005) in the primary tumor and shorter overall treatment time (OTT, p ϭ 0.046). A multivariate model including GTV primary , SUV max , equivalent radiation dose at 2 Gy corrected for time (EQD 2, T ) and OTT yielded an area under the curve assessed by the leave-one-out cross validation of 0.71 (95% CI, 0.65 -0.76). Conclusion . Our results confi rmed the validity of metabolic response assessment as a surrogate of survival. We developed a multivariate model that is able to identify patients at risk of residual disease. These patients may benefi t from an individualized and more adequate therapeutic approach, thereby improving local control and survival.
ObjectiveThe current pandemic has led to a proliferation of predictive models being developed to ... more ObjectiveThe current pandemic has led to a proliferation of predictive models being developed to address various aspects of COVID-19 patient care. We aimed to develop an online platform that would serve as an open source repository for a curated subset of such models, and provide a simple interface for included models to allow for online calculation. This platform would support doctors during decision-making regarding diagnoses, prognoses, and follow-up of COVID-19 patients, expediting the models’ transition from research to clinical practice.MethodsIn this proof-of-principle study, we performed a literature search in PubMed and WHO database to find suitable models for implementation on our platform. All selected models were publicly available (peer reviewed publications or open source repository) and had been validated (TRIPOD type 3 or 2b). We created a method for obtaining the regression coefficients if only the nomogram was available in the original publication. All predictive m...
Simple Summary Low–intermediate prostate cancer has a number of viable treatment options, such as... more Simple Summary Low–intermediate prostate cancer has a number of viable treatment options, such as radical prostatectomy and radiotherapy, with similar survival outcomes but different treatment-related side effects. The aim of this study is to facilitate patient-specific treatment selection by developing a decision support system (DSS) that incorporates predictive models for cancer-free survival and treatment-related side effects. We challenged this DSS by validating it against randomized clinical trials and assessing the benefit through a cost–utility analysis. We aim to expand upon the applications of this DSS by using it as the basis for an in silico clinical trial for an underrepresented patient group. This modeling study shows that DSS-based treatment decisions will result in a clinically relevant increase in the patients’ quality of life and can be used for in silico trials. Abstract The aim of this study is to build a decision support system (DSS) to select radical prostatecto...
A Practical Prediction Model for Overall Survival from Stage III Lung Cancer: a first step towards dose individualization
Lymphocyte-Sparing Radiotherapy: The Rationale for Protecting Lymphocyte-rich Organs When Combining Radiotherapy With Immunotherapy
Seminars in Radiation Oncology
Journal of Personalized Medicine
Background: Searching through the COVID-19 research literature to gain actionable clinical insigh... more Background: Searching through the COVID-19 research literature to gain actionable clinical insight is a formidable task, even for experts. The usefulness of this corpus in terms of improving patient care is tied to the ability to see the big picture that emerges when the studies are seen in conjunction rather than in isolation. When the answer to a search query requires linking together multiple pieces of information across documents, simple keyword searches are insufficient. To answer such complex information needs, an innovative artificial intelligence (AI) technology named a knowledge graph (KG) could prove to be effective. Methods: We conducted an exploratory literature review of KG applications in the context of COVID-19. The search term used was “covid-19 knowledge graph”. In addition to PubMed, the first five pages of search results for Google Scholar and Google were considered for inclusion. Google Scholar was used to include non-peer-reviewed or non-indexed articles such as...
Model-Based Cost-Effectiveness of Conventional and Innovative Chemo-Radiation in Lung Cancer
International Journal of Technology Assessment in Health Care
Introduction:Optimizing radiotherapy with or without chemotherapy through advanced imaging and ac... more Introduction:Optimizing radiotherapy with or without chemotherapy through advanced imaging and accelerated radiation schemes shows promising results in locally advanced non–small-cell lung cancer (NSCLC). This study compared the cost-effectiveness of positron emission tomography-computed tomography based isotoxic accelerated sequential chemo-radiation (SRT2) and concurrent chemo-radiation with daily low-dose cisplatin (CRT2) with standard sequential (SRT1) and concurrent chemo-radiation (CRT1).Methods:We used an externally validated mathematical model to simulate the four treatment strategies. The model was built using data from 200 NSCLC patients treated with curative sequential chemo-radiation. For concurrent strategies, data from a meta-analysis and a single study were included in the model. Costs, utilities, and resource use estimates were obtained from literature. Primary outcomes were the incremental cost-effectiveness and cost-utility ratio (ICUR) of each strategy. Scenario a...
Big Data-Based Decision Support Systems for Hadron Therapy
Advances in Particle Therapy
PLOS ONE
Background Prognostic models based on individual patient characteristics can improve treatment de... more Background Prognostic models based on individual patient characteristics can improve treatment decisions and outcome in the future. In many (radiomic) studies, small size and heterogeneity of datasets is a challenge that often limits performance and potential clinical applicability of these models. The current study is example of a retrospective multi-centric study with challenges and caveats. To highlight common issues and emphasize potential pitfalls, we aimed for an extensive analysis of these multi-center pre-treatment datasets, with an additional 18 F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/ CT) scan acquired during treatment. Methods The dataset consisted of 138 stage II-IV non-small cell lung cancer (NSCLC) patients from four different cohorts acquired from three different institutes. The differences between the cohorts were compared in terms of clinical characteristics and using the so-called 'cohort
Implications of Clinicians' Attitudes Towards Clinical Decision Support Systems
Studies in health technology and informatics, 2020
Proceeding of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD 08, 2008
Privacy-preserving data mining (PPDM) is an emergent research area that addresses the incorporati... more Privacy-preserving data mining (PPDM) is an emergent research area that addresses the incorporation of privacy preserving concerns to data mining techniques. In this paper we propose a privacy-preserving (PP) Cox model for survival analysis, and consider a real clinical setting where the data is horizontally distributed among different institutions. The proposed model is based on linearly projecting the data to a lower dimensional space through an optimal mapping obtained by solving a linear programming problem. Our approach differs from the commonly used random projection approach since it instead finds a projection that is optimal at preserving the properties of the data that are important for the specific problem at hand. Since our proposed approach produces an sparse mapping, it also generates a PP mapping that not only projects the data to a lower dimensional space but it also depends on a smaller subset of the original features (it provides explicit feature selection). Real data from several European healthcare institutions are used to test our model for survival prediction of non-small-cell lung cancer patients. These results are also confirmed using publicly available benchmark datasets. Our experimental results show that we are able to achieve a near-optimal performance without directly sharing the data across different data sources. This model makes it possible to conduct large-scale multi-centric survival analysis without violating privacy-preserving requirements.
Data from: Prognostic value of blood-biomarkers related to hypoxia, inflammation, immune response and tumour load in non-small cell lung cancer – a survival model with external validation
Purpose/Objective(s): Pneumonitis is one of the major treatment related toxicities from radiother... more Purpose/Objective(s): Pneumonitis is one of the major treatment related toxicities from radiotherapy for thoracic malignancies. Predictive factors for treatment related pneumonitis (TRP) are still controversial. The purpose of this study is to investigate whether the number of radiation treatment fields per fraction affects TRP among patients with non-small-cell lung cancer (NSCLC) receiving concurrent chemotherapy and 3-dimensional conformal radiation therapy (3D CRT). Materials/Methods: We determined the number of radiation treatment fields per fraction in 223 NSCLC patients who received definitive concurrent chemoradiation at our institution between 1998 and 2003. 3D CRT techniques were used in all patients. Clinical and dosimetric data of the patients were collected with the TRP graded using the NCI-CTC 3.0 criteria. Patients were categorized into 4 groups according to the number of fields per fraction: 2 fields, 3 fields, 4 fields and 5 fields or more. Patients with 2 fields per fraction were usually started with AP/PA followed by oblique beams. Dose-volume parameters for the normal lung including mean lung dose and volume of lung receiving above certain dose in each group of the patients were computed and compared using Kruskal-Wallis test. The actuarial incidence of TRP was calculated as the freedom from TRP within 18 months post-therapy. The risk of TRP was analyzed to evaluate the influence of the treatment fields per day using the log rank test. The mean lung doses were 22.0 ϩ/-6.4 Gy, 23.8 ϩ/-5.1 Gy, 21.6 ϩ/-5.5 Gy and 21.9 ϩ/-3.8 Gy for patients receiving 2,3,4 and 5 or more fields per fraction, respectively. There were no significant differences in the mean lung doses (pϭ0.115) or the distributions of the lung dose volume histograms among the four groups. In addition, the number of treatment fields irradiated per fraction had no significant influence on the freedom from TRP (p ϭ 0.738). We found no evidence that the number of radiation treatment fields per fractions affects the rate of TRP in NSCLC patients who received definitive concurrent chemoradiation. Further study is planned to identify any association between TRP and daily biological equivalent dose and irradiated volume of the lung, and to distinguish the severity of pulmonary injury caused by either low-dose high-volume versus high-dose low-volume treatments.
Radiotherapy and Oncology, 2010
Evidence is accumulating that radiotherapy of non-small cell lung cancer patients can be optimize... more Evidence is accumulating that radiotherapy of non-small cell lung cancer patients can be optimized by escalating the tumour dose until the normal tissue tolerances are met. To further improve the therapeutic ratio between tumour control probability and the risk of normal tissue complications, we firstly need to exploit inter patient variation. This variation arises, e.g. from differences in tumour shape and size, lung function and genetic factors. Secondly improvement is achieved by taking into account intra-tumour and intra-organ heterogeneity derived from molecular and functional imaging. Additional radiation dose must be delivered to those parts of the tumour that need it the most, e.g. because of increased radio-resistance or reduced therapeutic drug uptake, and away from regions inside the lung that are most prone to complication. As the delivery of these treatments plans is very sensitive for geometrical uncertainties, probabilistic treatment planning is needed to generate robust treatment plans. The administration of these complicated dose distributions requires a quality assurance procedure that can evaluate the treatment delivery and, if necessary, adapt the treatment plan during radiotherapy.
Radiotherapy and Oncology, 2009
Purpose: Extensive research has led to the identification of numerous dosimetric parameters as we... more Purpose: Extensive research has led to the identification of numerous dosimetric parameters as well as patient characteristics, associated with lung toxicity, but their clinical usefulness remains largely unknown. We investigated the predictive value of patient characteristics in combination with established dosimetric parameters. Patients and methods: Data from 438 lung cancer patients treated with (chemo)radiation were used. Lung toxicity was scored using the Common Toxicity Criteria version 3.0. A multivariate model as well as two single parameter models, including either V 20 or MLD, was built. Performance of the models was expressed as the AUC (Area Under the Curve). Results: The mean MLD was 13.5 Gy (SD 4.5 Gy), while the mean V 20 was 21.0% (SD 7.3%). Univariate models with V 20 or MLD both yielded an AUC of 0.47. The final multivariate model, which included WHO-performance status, smoking status, forced expiratory volume (FEV 1 ), age and MLD, yielded an AUC of 0.62 (95% CI: 0.55-0.69). Conclusions: Within the range of radiation doses used in our clinic, dosimetric parameters play a less important role than patient characteristics for the prediction of lung toxicity. Future research should focus more on patient-related factors, as opposed to dosimetric parameters, in order to identify patients at high risk for developing radiation-induced lung toxicity more accurately.
Tumor Volume Combined With Number of Positive Lymph Node Stations Is a More Important Prognostic Factor Than TNM Stage for Survival of Non–Small-Cell Lung Cancer Patients Treated With (Chemo)radiotherapy
International Journal of Radiation Oncology*Biology*Physics, 2008
The current tumor, node, metastasis system needs refinement to improve its ability to predict sur... more The current tumor, node, metastasis system needs refinement to improve its ability to predict survival of patients with non-small-cell lung cancer (NSCLC) treated with (chemo)radiation. In this study, we investigated the prognostic value of tumor volume and N status, assessed by using fluorodeoxyglucose-positron emission tomography (PET). Clinical data from 270 consecutive patients with inoperable NSCLC Stages I-IIIB treated radically with (chemo)radiation were collected retrospectively. Diagnostic imaging was performed using either integrated PET-computed tomography or computed tomography and PET separately. The Kaplan-Meier method, as well as Cox regression, was used to analyze data. Univariate survival analysis showed that number of positive lymph node stations (PLNSs), as well as N stage on PET, was associated significantly with survival. The final multivariate Cox model consisted of number of PLNSs, gross tumor volume (i.e., volume of the primary tumor plus lymph nodes), sex, World Health Organization performance status, and equivalent radiation dose corrected for time; N stage was no longer significant. Number of PLNSs, assessed by means of fluorodeoxyglucose-PET, was a significant factor for survival of patients with inoperable NSCLC treated with (chemo)radiation. Risk stratification for this group of patients should be based on gross tumor volume, number of PLNSs, sex, World Health Organization performance status, and equivalent radiation dose corrected for time.
European Journal of Cancer, 2007
Modelling antecedents of blood donation motivation among non-donors of varying age and education
British Journal of Psychology, 2009
Understanding blood donation motivation among non-donors is prerequisite to effective recruitment... more Understanding blood donation motivation among non-donors is prerequisite to effective recruitment. Two studies explored the psychological antecedents of blood donation motivation and the generalisability of a model of donation motivation across groups differing in age and educational level. An older well-educated population and a younger less well-educated population were sampled. The studies assessed the role of altruism, fear of blood/needles and donation-specific cognitions including attitudes and normative beliefs derived from an extended theory of planned behaviour (TPB). Across both samples, results showed that affective attitude, subjective norm, descriptive norm, and moral norm were the most important correlates of blood donation intentions. Self-efficacy was more important among the younger less well-educated group. Altruism was related to donation motivation but only indirectly through moral norm. Similarly, fear of blood/needles only had an indirect effect on motivation through affective attitude and self-efficacy. Additional analyses with the combined data set found no age or education moderation effects, suggesting that this core model of donation-specific cognitions can be used to inform future practical interventions recruiting new blood donors in the general population.
In this paper, we show that classical survival analysis involving censored data can naturally be ... more In this paper, we show that classical survival analysis involving censored data can naturally be cast as a ranking problem. The concordance index (CI), which quantifies the quality of rankings, is the standard performance measure for model assessment in survival analysis. In contrast, the standard approach to learning the popular proportional hazard (PH) model is based on Cox's partial likelihood. We devise two bounds on CI-one of which emerges directly from the properties of PH models-and optimize them directly. Our experimental results suggest that all three methods perform about equally well, with our new approach giving slightly better results. We also explain why a method designed to maximize the Cox's partial likelihood also ends up (approximately) maximizing the CI.
Acta Oncologica, 2010
Purpose . Metabolic response assessment is often used as a surrogate of local failure and surviva... more Purpose . Metabolic response assessment is often used as a surrogate of local failure and survival. Early identifi cation of patients with residual metabolic activity is essential as this enables selection of patients who could potentially benefi t from additional therapy. We report on the development of a pre-treatment prediction model for metabolic response using patient, tumor and treatment factors. Methods . One hundred and one patients with inoperable NSCLC (stage I-IV), treated with 3D conformal radical (chemo)-radiotherapy were retrospectively included in this study. All patients received a pre and post-radiotherapy fl uorodeoxyglucose positron emission tomography-computed tomography FDG-PET-CT scan. The electronic medical record system and the medical patient charts were reviewed to obtain demographic, clinical, tumor and treatment data. Primary outcome measure was examined using a metabolic response assessment on a postradiotherapy FDG-PET-CT scan. Radiotherapy was delivered in fractions of 1.8 Gy, twice a day, with a median prescribed dose of 60 Gy. Results . Overall survival was worse in patients with residual metabolic active areas compared with the patients with a complete metabolic response (p ϭ 0.0001). In univariate analysis, three variables were signifi cantly associated with residual disease: larger primary gross tumor volume (GTV primary , p ϭ 0.002), higher pre-treatment maximum standardized uptake value (SUV max , p ϭ 0.0005) in the primary tumor and shorter overall treatment time (OTT, p ϭ 0.046). A multivariate model including GTV primary , SUV max , equivalent radiation dose at 2 Gy corrected for time (EQD 2, T ) and OTT yielded an area under the curve assessed by the leave-one-out cross validation of 0.71 (95% CI, 0.65 -0.76). Conclusion . Our results confi rmed the validity of metabolic response assessment as a surrogate of survival. We developed a multivariate model that is able to identify patients at risk of residual disease. These patients may benefi t from an individualized and more adequate therapeutic approach, thereby improving local control and survival.
ObjectiveThe current pandemic has led to a proliferation of predictive models being developed to ... more ObjectiveThe current pandemic has led to a proliferation of predictive models being developed to address various aspects of COVID-19 patient care. We aimed to develop an online platform that would serve as an open source repository for a curated subset of such models, and provide a simple interface for included models to allow for online calculation. This platform would support doctors during decision-making regarding diagnoses, prognoses, and follow-up of COVID-19 patients, expediting the models’ transition from research to clinical practice.MethodsIn this proof-of-principle study, we performed a literature search in PubMed and WHO database to find suitable models for implementation on our platform. All selected models were publicly available (peer reviewed publications or open source repository) and had been validated (TRIPOD type 3 or 2b). We created a method for obtaining the regression coefficients if only the nomogram was available in the original publication. All predictive m...
Simple Summary Low–intermediate prostate cancer has a number of viable treatment options, such as... more Simple Summary Low–intermediate prostate cancer has a number of viable treatment options, such as radical prostatectomy and radiotherapy, with similar survival outcomes but different treatment-related side effects. The aim of this study is to facilitate patient-specific treatment selection by developing a decision support system (DSS) that incorporates predictive models for cancer-free survival and treatment-related side effects. We challenged this DSS by validating it against randomized clinical trials and assessing the benefit through a cost–utility analysis. We aim to expand upon the applications of this DSS by using it as the basis for an in silico clinical trial for an underrepresented patient group. This modeling study shows that DSS-based treatment decisions will result in a clinically relevant increase in the patients’ quality of life and can be used for in silico trials. Abstract The aim of this study is to build a decision support system (DSS) to select radical prostatecto...
A Practical Prediction Model for Overall Survival from Stage III Lung Cancer: a first step towards dose individualization
Lymphocyte-Sparing Radiotherapy: The Rationale for Protecting Lymphocyte-rich Organs When Combining Radiotherapy With Immunotherapy
Seminars in Radiation Oncology
Journal of Personalized Medicine
Background: Searching through the COVID-19 research literature to gain actionable clinical insigh... more Background: Searching through the COVID-19 research literature to gain actionable clinical insight is a formidable task, even for experts. The usefulness of this corpus in terms of improving patient care is tied to the ability to see the big picture that emerges when the studies are seen in conjunction rather than in isolation. When the answer to a search query requires linking together multiple pieces of information across documents, simple keyword searches are insufficient. To answer such complex information needs, an innovative artificial intelligence (AI) technology named a knowledge graph (KG) could prove to be effective. Methods: We conducted an exploratory literature review of KG applications in the context of COVID-19. The search term used was “covid-19 knowledge graph”. In addition to PubMed, the first five pages of search results for Google Scholar and Google were considered for inclusion. Google Scholar was used to include non-peer-reviewed or non-indexed articles such as...
Model-Based Cost-Effectiveness of Conventional and Innovative Chemo-Radiation in Lung Cancer
International Journal of Technology Assessment in Health Care
Introduction:Optimizing radiotherapy with or without chemotherapy through advanced imaging and ac... more Introduction:Optimizing radiotherapy with or without chemotherapy through advanced imaging and accelerated radiation schemes shows promising results in locally advanced non–small-cell lung cancer (NSCLC). This study compared the cost-effectiveness of positron emission tomography-computed tomography based isotoxic accelerated sequential chemo-radiation (SRT2) and concurrent chemo-radiation with daily low-dose cisplatin (CRT2) with standard sequential (SRT1) and concurrent chemo-radiation (CRT1).Methods:We used an externally validated mathematical model to simulate the four treatment strategies. The model was built using data from 200 NSCLC patients treated with curative sequential chemo-radiation. For concurrent strategies, data from a meta-analysis and a single study were included in the model. Costs, utilities, and resource use estimates were obtained from literature. Primary outcomes were the incremental cost-effectiveness and cost-utility ratio (ICUR) of each strategy. Scenario a...
Big Data-Based Decision Support Systems for Hadron Therapy
Advances in Particle Therapy
PLOS ONE
Background Prognostic models based on individual patient characteristics can improve treatment de... more Background Prognostic models based on individual patient characteristics can improve treatment decisions and outcome in the future. In many (radiomic) studies, small size and heterogeneity of datasets is a challenge that often limits performance and potential clinical applicability of these models. The current study is example of a retrospective multi-centric study with challenges and caveats. To highlight common issues and emphasize potential pitfalls, we aimed for an extensive analysis of these multi-center pre-treatment datasets, with an additional 18 F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/ CT) scan acquired during treatment. Methods The dataset consisted of 138 stage II-IV non-small cell lung cancer (NSCLC) patients from four different cohorts acquired from three different institutes. The differences between the cohorts were compared in terms of clinical characteristics and using the so-called 'cohort