Survival Analysis Part IV: Further concepts and methods in survival analysis

Clark, Taane G.; Bradburn, Michael; Love, Sharon; Altman, Douglas G.

doi:10.1038/sj.bjc.6601117

Cited by 152 publications

(101 citation statements)

References 39 publications

(28 reference statements)

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“…A simple sensitivity analysis was conducted in which the worst-case and the best-case scenarios were imputed for the 11 participants lost to follow-up. 19 The worstcase scenario assumed that all 11 died one day after discharge. The best-case scenario assumed that all 11 were alive on 31 December 2014.…”

Section: Discussionmentioning

confidence: 99%

Two-year survival following discharge from hospital after spinal cord injury in Bangladesh

et al. 2015

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Study design: Mixed retrospective-prospective cohort study. Objectives: To determine 2-year survival following discharge from hospital after spinal cord injury in Bangladesh. Setting: Bangladesh. Methods: Medical records were used to identify all patients admitted in 2011 with a recent spinal cord injury to the Centre for Rehabilitation of the Paralysed, a large Bangladeshi hospital that specialises in care of people with spinal cord injury. Patients or their families were subsequently visited or contacted by telephone in 2014. Vital status and, where relevant, date and cause of death were determined by verbal autopsy. Results: 350 of 371 people admitted with a recent spinal cord injury in 2011 were discharged alive from hospital. All but eleven were accounted for two years after discharge (97% follow-up). Two-year survival was 87% (95% CI 83% to 90%). Two-year survival of those who were wheelchair-dependent was 81% (95% CI 76% to 86%). The most common cause of death was sepsis due to pressure ulcers. Conclusion: In Bangladesh, approximately one in five people with spinal cord injury who are wheelchair-dependent die within two years of discharge from hospital. Most deaths are due to sepsis from potentially preventable pressure ulcers.

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Section: Discussionmentioning

confidence: 99%

Two-year survival following discharge from hospital after spinal cord injury in Bangladesh

et al. 2015

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“…As the comparison between negativity and positivity was performed for descriptive purposes only, rather than for the analysis of clinical endpoints, the selection of the median value as cut-off score was based on evaluation of the distribution of HOXD13 scores and is commonly used to describe semiquantitative measurements. 33 Differences in the number of negative and positive cases were analyzed using a test of equal proportions.…”

Section: Discussionmentioning

confidence: 99%

HOX D13 expression across 79 tumor tissue types

Cantile

Franco

Tschan

et al. 2009

Intl Journal of Cancer

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HOX genes control normal development, primary cellular processes and are characterized by a unique genomic network organization. Locus D HOX genes play an important role in limb generation and mesenchymal condensation. Dysregulated HOXD13 expression has been detected in breast cancer, melanoma, cervical cancer and astrocytomas. We have investigated the epidemiology of HOXD13 expression in human tissues and its potential deregulation in the carcinogenesis of specific tumors. HOXD13 homeoprotein expression has been detected using microarray technology comprising more than 4,000 normal and neoplastic tissue samples including 79 different tumor categories. Validation of HOXD13 expression has been performed, at mRNA level, for selected tumor types. Significant differences are detectable between specific normal tissues and corresponding tumor types with the majority of cancers showing an increase in HOXD13 expression (16.1% normal vs. 57.7% cancers). In contrast, pancreas and stomach tumor subtypes display the opposite trend. Interestingly, detection of the HOXD13 homeoprotein in pancreas-tissue microarrays shows that its negative expression has a significant and adverse effect on the prognosis of patients with pancreatic cancer independent of the T or N stage at the time of diagnosis. Our study provides, for the first time, an overview of a HOX protein expression in a large series of normal and neoplastic tissue types, identifies pancreatic cancer as one of the most affected by the HOXD13 hoemoprotein and underlines the way homeoproteins can be associated to human cancerogenesis. ' UICCKey words: HOXD13; HOX and multitumor tissue microarray; HOXD13 and pancreas Class I Homeobox genes (Hox, mice; HOX, human) are transcription factors mostly involved in embryonic development. 1 They display an unique genomic network organization: 4 compact chromosomal loci (HOXA at 7p15.3, HOXB at 17q21.3, HOXC at 12q13.3 and HOXD at 2q31 2 ) where 39 sequence corresponding genes can be aligned with each other into 13 antero-posterior paralogous groups. The HOX gene network, the most repeat-poor regions in the human genome, 3 is also expressed in normal adult human organs. 4 HOX genes appear to regulate phenotype cell identity, 5,6 cell differentiation 7,8 and control primary cellular processes, as proven by the description of congenital, 9 somatic 10 and metabolic 11 diseases involving these genes. Furthermore, besides the already established role of the HOX network in hematopoiesis and leukemogenesis, 12 HOX genes are implicated in the neoplastic alterations of human solid tissues and organs such as kidney, colon, lung, skin, bladder, liver, breast and prostate. 13,14 New crucial functions have recently been ascribed to HOX genes and homeoproteins mostly related to their interaction with miRNAs and ncRNAs to guarantee transcription and export of specific mRNAs. 15,16 Locus D HOX genes are localized on chromosome 2q31-32 and play a role, with its posterior paralogous genes, in limb and digit generation during embryonic development 1...

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“…This may create scientifically unrealistic models because this procedure discards potentially important information since all values between the cutoff levels have an equal effect on the model. Therefore, categorization considerably lowers the statistical test-power and can be seen as an introduction of measurement errors (8)(9)(10)(11)(12)(13)(14).…”

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confidence: 99%

“…Categorization of a variable which can be continuously measured should be done only exceptionally. For instance, when precise measurement is difficult, the distribution of the variable is highly skewed or its relation with another variable is nonlinear (8,10,17).…”

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confidence: 99%