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Development and validation of nomogram estimating post-surgery hospital stay of lung cancer patients: relevance for predictive, preventive, and personalized healthcare strategies.

ABSTRACT: Objective:In the era of fast track surgery, early and accurately estimating whether postoperative length of stay (p-LOS) will be prolonged after lung cancer surgery is very important, both for patient's discharge planning and hospital bed management. Pulmonary function tests (PFTs) are very valuable routine examinations which should not be underutilized before lung cancer surgery. Thus, this study aimed to establish an accurate but simple prediction tool, based on PFTs, for achieving a personalized prediction of prolonged p-LOS in patients following lung resection. Methods:The medical information of 1257 patients undergoing lung cancer surgery were retrospectively reviewed and served as the training set. p-LOS exceeding the third quartile value was considered prolonged. Using logistic regression analyses, potential predictors of prolonged p-LOS were identified among various preoperative factors containing PFTs and intraoperative factors. A nomogram was constructed and subjected to internal and external validation. Results:Five independent risk factors for prolonged p-LOS were identified, including older age, being male, and ratio of residual volume to total lung capacity (RV/TLC)???45.0% which is the only modifiable risk factor, more invasive surgical approach, and surgical type. The nomogram comprised of these five predictors exhibited sufficient predictive accuracy, with the area under the receiver operating characteristic curve (AUC) of 0.76 [95% confidence interval (CI) 0.73-0.79] in the internal validation. Also its predictive performance remained fine in the external validation, with the AUC of 0.70 (95% CI 0.60-0.79). The calibration curves showed satisfactory agreements between the model predicted probability and the actually observed probability. Conclusions:Preoperative amelioration of RV/TLC may prevent lung cancer patients from unnecessary prolonged p-LOS. The integrated nomogram we developed could provide personalized risk prediction of prolonged p-LOS. This prediction tool may help patients perceive expected hospital stays and enable clinicians to achieve better bed management after lung cancer surgery.

SUBMITTER: Hu XL

PROVIDER: S-EPMC6562016 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

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Development and validation of nomogram estimating post-surgery hospital stay of lung cancer patients: relevance for predictive, preventive, and personalized healthcare strategies.

Hu Xiang-Lin XL Xu Song-Tao ST Wang Xiao-Cen XC Luo Jin-Long JL Hou Dong-Ni DN Zhang Xiao-Min XM Bao Chen C Yang Dong D Song Yuan-Lin YL Bai Chun-Xue CX

The EPMA journal 20190508 2

<h4>Objective</h4>In the era of fast track surgery, early and accurately estimating whether postoperative length of stay (p-LOS) will be prolonged after lung cancer surgery is very important, both for patient's discharge planning and hospital bed management. Pulmonary function tests (PFTs) are very valuable routine examinations which should not be underutilized before lung cancer surgery. Thus, this study aimed to establish an accurate but simple prediction tool, based on PFTs, for achieving a p ...[more]

PMID: 31258821

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Project description:ObjectiveIn an era of increasingly expensive intensive care costs, it is essential to evaluate early whether the length of stay (LOS) in the intensive care unit (ICU) of obesity patients with sepsis will be prolonged. On the one hand, it can reduce costs; on the other hand, it can reduce nosocomial infection. Therefore, this study aimed to verify whether ICU prolonged LOS was significantly associated with poor prognosis poor in obesity patients with sepsis and develop a simple prediction model to personalize the risk of ICU prolonged LOS for obesity patients with sepsis.MethodIn total, 14,483 patients from the eICU Collaborative Research Database were randomized to the training set (3,606 patients) and validation set (1,600 patients). The potential predictors of ICU prolonged LOS among various factors were identified using logistic regression analysis. For internal and external validation, a nomogram was developed and performed.ResultsICU prolonged LOS was defined as the third quartile of ICU LOS or more for all sepsis patients and demonstrated to be significantly associated with the mortality in ICU by logistic regression analysis. When entering the ICU, seven independent risk factors were identified: maximum white blood cell, minimum white blood cell, use of ventilation, Glasgow Coma Scale, minimum albumin, maximum respiratory rate, and minimum red blood cell distribution width. In the internal validation set, the area under the curve was 0.73, while in the external validation set, it was 0.78. The calibration curves showed that this model predicted probability due to actually observed probability. Furthermore, the decision curve analysis and clinical impact curve showed that the nomogram had a high clinical net benefit.ConclusionIn obesity patients with sepsis, we created a novel nomogram to predict the risk of ICU prolonged LOS. This prediction model is accurate and reliable, and it can assist patients and clinicians in determining prognosis and making clinical decisions.

Project description:Background and pppm-related working hypothesisIn the diagnosis of incomplete rotator cuff injuries (IRCI), magnetic resonance imaging (MRI) and ultrasound examination often have false-positive and false-negative results, while arthroscopy is expensive, invasive, and complex. From the strategy of predictive, preventive, and personalized medicine (PPPM), shoulder anatomical characteristics based on MRI have been demonstrated to accurately predict IRCI and their clinical applicability for personalized prediction of IRCI.AimsThis study aimed to develop and validate a nomogram based on anatomical features of the shoulder on MRI to identify IRCI for PPPM healthcare strategies.MethodsThe medical information of 257 patients undergoing preoperative MRI examination was retrospectively reviewed and served as the primary cohort. Partial-thickness rotator cuff tears (RCTs) and tendinopathy observed under arthroscopy were considered IRCI. Using logistic regression analyses and least absolute shrinkage and selection operator (LASSO), IRCI was identified among various preoperative factors containing shoulder MRI and clinical features. A nomogram was constructed and subjected to internal and external validations (80 patients).ResultsThe following eight independent risk factors for IRCI were identified:AgeThe left injured sidesThe Goutallier classification of supraspinatus in oblique coronal positionThe Goutallier classification of supraspinatus in the axial positionAcromial thicknessAcromiohumeral distanceCoracohumeral distanceAbnormal acromioclavicular joint signalsThe nomogram accurately predicted IRCI in the development (C-index, 0.932 (95% CI, 0.891, 0.973)) and validation (C-index, 0.955 (95% CI, 0.918, 0.992)) cohorts. The calibration curve was consistent between the predicted IRCI probability and the actual IRCI ratio of the nomogram. The decision curve analysis and clinical impact curves demonstrated that the model had high clinical applicability.ConclusionsEight independent factors that accurately predicted IRCI were determined using MRI anatomical findings. These personalized factors can prevent unnecessary diagnostic interventions (e.g., arthroscopy) and can assist surgeons in implementing individualized clinical decisions in medical practice, thus addressing the goals of PPPM.Supplementary informationThe online version contains supplementary material available at 10.1007/s13167-023-00333-5.

Project description:BackgroundQuantification of motor performance has a promising role in personalized medicine by diagnosing and monitoring, e.g. neurodegenerative diseases or health problems related to aging. New motion assessment technologies can evolve into patient-centered eHealth applications on a global scale to support personalized healthcare as well as treatment of disease. However, uncertainty remains on the limits of generalizability of such data, which is relevant specifically for preventive or predictive applications, using normative datasets to screen for incipient disease manifestations or indicators of individual risks.ObjectiveThis study explored differences between healthy German and Japanese adults in the performance of a short set of six motor tests.MethodsSix motor tasks related to gait and balance were recorded with a validated 3D camera system. Twenty-five healthy adults from Chiba, Japan, participated in this study and were matched for age, sex, and BMI to a sample of 25 healthy adults from Berlin, Germany. Recordings used the same technical setup and standard instructions and were supervised by the same experienced operator. Differences in motor performance were analyzed using multiple linear regressions models, adjusted for differences in body stature.ResultsFrom 23 presented parameters, five showed group-related differences after adjustment for height and weight (R 2 between .19 and .46, p<.05). Japanese adults transitioned faster between sitting and standing and used a smaller range of hand motion. In stepping-in-place, cadence was similar in both groups, but Japanese adults showed higher knee movement amplitudes. Body height was identified as relevant confounder (standardized beta >.5) for performance of short comfortable and maximum speed walks. For results of posturography, regression models did not reveal effects of group or body stature.ConclusionsOur results support the existence of a population-specific bias in motor function patterns in young healthy adults. This needs to be considered when motor function is assessed and used for clinical decisions, especially for personalized predictive and preventive medical purposes. The bias affected only the performance of specific items and parameters and is not fully explained by population-specific ethnic differences in body stature. It may be partially explained as cultural bias related to motor habits. Observed effects were small but are expected to be larger in a non-controlled cross-cultural application of motion assessment technologies with relevance for related algorithms that are being developed and used for data processing. In sum, the interpretation of individual data should be related to appropriate population-specific or even better personalized normative values to yield its full potential and avoid misinterpretation.Supplementary informationThe online version contains supplementary material available at 10.1007/s13167-021-00236-3.

Project description:BackgroundSeveral ocular factors have been identified for primary angle-closure glaucoma (PACG), such as a small cornea, elevated intraocular pressure (IOP), shallow anterior chamber, and short axial length (AL). However, the relationship between the severity of PACG and various ocular parameters [IOP, anterior chamber depth, AL, central corneal thickness] is not fully understood.MethodsA 7-year cross-sectional study. A total of 2254 eyes of 1312 PACG patients (females = 856 [1479 eyes] and males = 456 [775 eyes]) were included. A detailed eye examination was performed. The participants were categorized into gender subgroups followed by subdivision into three different severity groups according to their mean deviation (MD) of the visual fields results as follows: mild (MD ≤ 6 dB), moderate (MD 6-12 dB), and severe (MD > 12 dB) PACG. The associations of ocular biometry with severity of PACG were analyzed using paired Student's t test, multivariate linear regression, and logistic regression analysis.ResultsThere was a significant positive correlation between the MD and AL in the female subgroup (B = 0.663, p = 0.001, 95%CI = 1.070 to 1.255) but not in the male subgroup. Increased AL levels (mild [OR = 1], moderate [OR = 1.047, p = 0.062, 95%CI = 0.947 to 2.462], and severe [OR = 1.274, p < 0.001, 95%CI = 1.114 to 1.457]) were only associated with the severity of PACG in females. Paired Student's t tests showed that the long AL female eyes have a higher MD value than in the short AL female eyes (mean difference = 3.09, t = 6.846, p < 0.001) in the same subjects, but not in the male subgroup (p = 0.648).ConclusionsThe AL was positively and significantly related to the severity of PACG in female but not male subjects. This finding refers to the PACG pathogenesis and suggests the use of AL assessment in glaucoma monitoring, diagnosis, and progression. This may contribute to further development of personalized strategies in preventive medicine.

Project description:BackgroundThere is increasing research interest in the development of preventive treatment for individuals at risk of rheumatoid arthritis (RA). Previous studies have explored the perceptions of at-risk groups and patients about predictive and preventive strategies for RA, but little is known about health care professionals' (HCPs) perspectives.MethodsOne-to-one semi-structured qualitative interviews were conducted (face-to-face or by telephone) with HCPs. Audio recordings of the interviews were transcribed, and the data were analysed by thematic analysis.ResultsNineteen HCPs (11 female) were interviewed, including ten GPs, six rheumatologists and three rheumatology nurse specialists. The thematic analysis identified four organising themes: 1) Attributes of predictive and preventive approaches; 2) Ethical and psychological concerns; 3) Implementation issues and 4) Learning from management of other conditions. Theme 1 described necessary attributes of predictive and preventive approaches, including the type and performance of predictive tools, the need for a sound evidence base and consideration of risks and benefits associated with preventive treatment. Theme 2 described the ethical and psycho-social concerns that interviewees raised, including the potential negative economic, financial and psychological effects of risk disclosure for 'at-risk' individuals, uncertainty around the development of RA and the potential for benefit associated with the treatments being considered. Theme 3 describes the implementation issues considered, including knowledge and training needs, costs and resource implications of implementing predictive and preventive approaches, the role of different types of HCPs, guidelines and tools needed, and patient characteristics relating to the appropriateness of preventive treatments. Theme 4 describes lessons that could be learned from interviewees' experiences of prediction and prevention in other disease areas, including how preventive treatment is prescribed, existing guidelines and tools for other diseases and issues relating to risk communication.ConclusionsFor successful implementation of predictive and preventative approaches in RA, HCPs need appropriate training about use and interpretation of predictive tools, communication of results to at-risk individuals, and options for intervention. Evidence of cost-efficiency, appropriate resource allocation, adaptation of official guidelines and careful consideration of the at-risk individuals' psycho-social needs are also needed.

Project description:BackgroundAtherosclerosis is a major contributor to morbidity and mortality worldwide. Although several molecular markers associated with atherosclerosis have been developed in recent years, the lack of robust evidence hinders their clinical applications. For these reasons, identification of novel and robust biomarkers will directly contribute to atherosclerosis management in the context of predictive, preventive, and personalized medicine (PPPM). This integrative analysis aimed to identify critical genetic markers of atherosclerosis and further explore the underlying molecular immune mechanism attributing to the altered biomarkers.MethodsGene Expression Omnibus (GEO) series datasets were downloaded from GEO. Firstly, differential expression analysis and functional analysis were conducted. Multiple machine-learning strategies were then employed to screen and determine key genetic markers, and receiver operating characteristic (ROC) analysis was used to assess diagnostic value. Subsequently, cell-type identification by estimating relative subsets of RNA transcript (CIBERSORT) and a single-cell RNA sequencing (scRNA-seq) data were performed to explore relationships between signatures and immune cells. Lastly, we validated the biomarkers' expression in human and mice experiments.ResultsA total of 611 overlapping differentially expressed genes (DEGs) included 361 upregulated and 250 downregulated genes. Based on the enrichment analysis, DEGs were mapped in terms related to immune cell involvements, immune activating process, and inflaming signals. After using multiple machine-learning strategies, dehydrogenase/reductase 9 (DHRS9) and protein tyrosine phosphatase receptor type J (PTPRJ) were identified as critical biomarkers and presented their high diagnostic accuracy for atherosclerosis. From CIBERSORT analysis, both DHRS9 and PTPRJ were significantly related to diverse immune cells, such as macrophages and mast cells. Further scRNA-seq analysis indicated DHRS9 was specifically upregulated in macrophages of atherosclerotic lesions, which was confirmed in atherosclerotic patients and mice.ConclusionsOur findings are the first to report the involvement of DHRS9 in the atherogenesis, and the proatherogenic effect of DHRS9 is mediated by immune mechanism. In addition, we confirm that DHRS9 is localized in macrophages within atherosclerotic plaques. Therefore, upregulated DHRS9 could be a novel potential target for the future predictive diagnostics, targeted prevention, patient stratification, and personalization of medical services in atherosclerosis.Supplementary informationThe online version contains supplementary material available at 10.1007/s13167-022-00289-y.

Dataset Information

Development and validation of nomogram estimating post-surgery hospital stay of lung cancer patients: relevance for predictive, preventive, and personalized healthcare strategies.

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Development and validation of nomogram estimating post-surgery hospital stay of lung cancer patients: relevance for predictive, preventive, and personalized healthcare strategies.

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