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Survival analysis: part II - applied clinical data analysis.

ABSTRACT: As a follow-up to a previous article, this review provides several in-depth concepts regarding a survival analysis. Also, several codes for specific survival analysis are listed to enhance the understanding of such an analysis and to provide an applicable survival analysis method. A proportional hazard assumption is an important concept in survival analysis. Validation of this assumption is crucial for survival analysis. For this purpose, a graphical analysis method and a goodnessof- fit test are introduced along with detailed codes and examples. In the case of a violated proportional hazard assumption, the extended models of a Cox regression are required. Simplified concepts of a stratified Cox proportional hazard model and time-dependent Cox regression are also described. The source code for an actual analysis using an available statistical package with a detailed interpretation of the results can enable the realization of survival analysis with personal data. To enhance the statistical power of survival analysis, an evaluation of the basic assumptions and the interaction between variables and time is important. In doing so, survival analysis can provide reliable scientific results with a high level of confidence.

SUBMITTER: In J

PROVIDER: S-EPMC6781220 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

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Survival analysis: part II - applied clinical data analysis.

In Junyong J Lee Dong Kyu DK

Korean journal of anesthesiology 20190517 5

As a follow-up to a previous article, this review provides several in-depth concepts regarding a survival analysis. Also, several codes for specific survival analysis are listed to enhance the understanding of such an analysis and to provide an applicable survival analysis method. A proportional hazard assumption is an important concept in survival analysis. Validation of this assumption is crucial for survival analysis. For this purpose, a graphical analysis method and a goodnessof- fit test ar ...[more]

PMID: 31096731

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Project description:Knowledge on the outcome of C2-fractures is founded on heterogenous samples with cross-sectional outcome assessment focusing on union rates, complications and technical concerns related to surgical treatment. Reproducible clinical and functional outcome assessments are scant. Validated generic and disease specific outcome measures were rarely applied. Therefore, the aim of the current study is to investigate the radiographic, functional and clinical outcome of a patient sample with C2-fractures. Out of a consecutive series of 121 patients with C2 fractures, 44 met strict inclusion criteria and 35 patients with C2-fractures treated either nonsurgically or surgically with motion-preserving techniques were surveyed. Outcome analysis included validated measures (SF-36, NPDI, CSOQ), and a functional CT-scanning protocol for the evaluation of C1-2 rotation and alignment. Mean follow-up was 64 months and mean age of patients was 52 years. Classification of C2-fractures at injury was performed using a detailed morphological description: 24 patients had odontoid fractures type II or III, 18 patients had fracture patterns involving the vertebral body and 11 included a dislocated or a burst lateral mass fracture. Thirty-one percent of patients were treated with a halo, 34% with a Philadelphia collar and 34% had anterior odontoid screw fixation. At follow-up mean atlantoaxial rotation in left and right head position was 20.2 degrees and 20.6 degrees, respectively. According to the classification system of posttreatment C2-alignment established by our group in part I of the C2-fracture study project, mean malunion score was 2.8 points. In 49% of patients the fractures healed in anatomical shape or with mild malalignment. In 51% fractures healed with moderate or severe malalignment. Self-rated outcome was excellent or good in 65% of patients and moderate or poor in 35%. The raw data of varying nuances allow for comparison in future benchmark studies and metaanalysis. Detailed investigation of C2-fracture morphology, posttreatment C2-alignment and atlantoaxial rotation allowed a unique outcome analysis that focused on the identification of risk factors for poor outcome and the interdependencies of outcome variables that should be addressed in studies on C2-fractures. We recognized that reduced rotation of C1-2 per se was not a concern for the patients. However, patients with worse clinical outcomes had reduced total neck rotation and rotation C1-2. In turn, C2-fractures, especially fractures affecting the lateral mass that healed with atlantoaxial deformity and malunion, had higher incidence of atlantoaxial degeneration and osteoarthritis. Patients with increased severity of C2-malunion and new onset atlantoaxial arthritis had worse clinical outcomes and significantly reduced rotation C1-2. The current study offers detailed insight into the radiographical, functional and clinical outcome of C2-fractures. It significantly adds to the understanding of C2-fractures.

Project description:The investigation of cortical porosity is an important aspect of understanding biological, pathoetiological, and biomechanical processes occurring within the skeleton. With the emergence of HR-pQCT as a noninvasive tool suitable for clinical use, cortical porosity at appendicular sites can be directly visualized in vivo. The aim of this study was to introduce a novel topological analysis of the cortical pore network for HR-pQCT data and determine the influence of resolution on measures of cortical pore network microstructure and topology.Cadaveric radii were scanned using HR-pQCT at two different voxel sizes (41 and 82 μm) and also using μCT at a voxel size of 18 μm. HR-pQCT and μCT image sets were spatially coregistered. Segmentation and quantification of cortical porosity (Ct.Po) and mean pore diameter (Ct.Po.Dm) were achieved using an established extended cortical analysis technique. Topological classification of individual pores was performed using topology-preserving skeletonization and multicolor dilation algorithms. Based on the pore skeleton topological classification, the following parameters were quantified: total number of planar surface-skeleton canals (N.Slabs), tubular curve-skeleton canals (N.Tubes), and junction elements (N.Junctions), mean slab volume (Slab.Vol), mean tube volume (Tube.Vol), mean slab orientation (Slab.θ), mean tube orientation (Tube.θ), N.Slabs/N.Tubes, and integral (total) slab volume/integral tube volume (iSlab.Vol/iTube.Vol). An in vivo reproducibility study was also conducted to assess short-term precision of the topology parameters. Precision error was characterized using root mean square coefficient of variation (RMSCV%).Correlations to μCT values for Ct.Po were significant for both the 41 and 82 μm HR-pQCT data (41: r(2) = 0.82, p < 0.001, 82: r(2) = 0.75, p < 0.001). For Ct.Po.Dm, only the 41 μm data were significantly predictive of μCT values (r(2) = 0.72, p < 0.01) Data at both HR-pQCT voxel sizes were strongly predictive of the μCT values for N.Slabs (41: r(2) = 0.93, p < 0.001; 82: r(2) = 0.84, p < 0.001), N.Tubes (41: r(2) = 0.94, p < 0.001; 82: r(2) = 0.84, p < 0.001), and N.Junctions (41: r(2) = 0.93, p < 0.001; 82: r(2) = 0.78, p < 0.001), though proportional bias was evident in these correlations. Weak correlations were seen for iSlab.Vol/iTube.Vol at both voxel sizes (41: r(2) = 0.52, p < 0.01; 82: r(2) = 0.39, p < 0.05). Slab.Vol was significantly correlated to μCT data at 41 μm (r(2) = 0.60, p < 0.01) but not at 82 μm, while Tube.Vol was significantly correlated at both voxel sizes (41: r(2) = 0.79, p < 0.001; 82: r(2) = 0.68, p < 0.01). In vivo precision error for these parameters ranged from 2.31 to 9.68 RMSCV%.Strong correlations between μCT- and HR-pQCT-derived measurements were found, particularly in HR-pQCT images obtained at 41 μm. These data are in agreement with our previous study investigating the effect of voxel size on standard HR-pQCT metrics of trabecular and cortical microstructure, and extend our previous findings to include topological descriptors of the cortical pore network.

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Survival analysis: part II - applied clinical data analysis.

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Survival analysis: part II - applied clinical data analysis.

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