Multivariate model
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PURPOSE OF THE STUDY: The primary aim of the study was to identify characteristics predicting the blood loss associated with primary total hip (THA) and knee (TKA) arthroplasty surgery. The other objective was to find out which characteristics were important for peri-operative allogeneic blood transfusion in the same group of patients. MATERIAL AND METHODS: This prospective study comprised 210 consecutive patients who underwent primary THA (n = 115) or primary TKA (n = 95) at our department. In each patient, 21 pre-operative and peri-operative characteristics were recorded. Of them, the following characteristics were selected for statistical evaluation: age, gender, BMI, primary diagnosis, Charlson co-morbidity score, type of prophylaxis for deep-vein thrombosis, type of implant fixation (in THA), pre-operative INR value, haematocrit, haemoglobin (Hb) and platelet levels, amount of autologous blood donated by the patient, ASA score, operative time, use of tourniquet (in TKA), type of anaesthesia used, blood recuperation and patient's smoking habits. Multivariate analysis was used as the statistical method. For hypothesis testing, a statistical significance level of 0.05 was stated and, for enclosing (removing) characteristics to (from) multivariate models, the significance level was set at 0.11. RESULTS: The group included 81 men and 129 women; the mean age at the time of surgery was 65.5 ± 11.97 years (mean±SD) in the THA patients and 68.5 ± 8.52 years in the TKA patients. Primary osteoarthritis was the most frequent surgical diagnosis (THA, 64.35%; TKA, 82.1%). The mean amount of blood loss was 1258 ± 402.6 ml in THA and 1580 ± 475.5 ml in TKA. The mean amount of allogeneic blood required was 130 ± 202 ml when all THA patients were considered, and 371.95 ± 159.3 ml when only those who received it were involved. For the TKA patients, the corresponding values were 160.1 ± 278.8 ml for all patients and 507 ± 264.5 ml for blood recipients only. The characteristics that affected the amount of blood loss in THA included BMI, ASA score, blood recuperation, type of anaesthesia, and smoking habits; in TKA these were BMI, pre-operative platelet count, INR and type of anaesthesia. High pre-operative Hb levels made the probability of allogeneic blood requirement lower in both THA and TKA. Autotransfusion decreased the probability of allogeneic blood requirements only in THA. DISCUSSION That the pre-operative Hb level is the strongest predictor for the probability of allogeneic blood transfusion during both THA and TKA is a logical and well-known fact. What remains to be established is the optimal protocol for pre-operative preparation of the patients with low Hb levels undergoing elective replacement (hip and knee) surgery. This study clearly showed that, in THA patients, pre-operative autologous blood donation decreased the probability of allogeneic blood transfusion. Other results of our multivariate analyses were not clinically unambiguous and therefore further research on a larger patient group is warranted. Such studies will also require the development of a more exact method for the assessment of blood loss at the operating theatre. CONCLUSION: The patients with low pre-operative Hb levels have a high probability that they will require allogeneic blood transfusion during primary THA and TKA. Autologous blood donation can decrease this probability significantly (here proved only for THA patients). The multivariate model of blood loss published here could assist in estimation of peri-operative blood loss and potential risk of blood transfusion requirements.
AIM: The first aim of this study was to search for new biomarkers to be used in gastric cancer diagnostics. The second aim was to verify the findings presented in literature on a sample of the local population and investigate the risk of gastric cancer in that population using a multivariant statistical analysis. PATIENTS AND METHODS: We assessed a group of 36 patients with gastric cancer and 69 healthy individuals. We determined carcinoembryonic antigen, cancer antigen 19-9, cancer antigen 72-4, matrix metalloproteinases (-1, -2, -7, -8 and -9), osteoprotegerin, osteopontin, prothrombin induced by vitamin K absence-II, pepsinogen I, pepsinogen II, gastrin and Helicobacter pylori for each sample. RESULTS: The multivariate stepwise logistic regression identified the following biomarkers as the best gastric cancer predictors: CEA, CA72-4, pepsinogen I, Helicobacter pylori presence and MMP7. CONCLUSION: CEA and CA72-4 remain the best markers for gastric cancer diagnostics. We suggest a mathematical model for the assessment of risk of gastric cancer.
- MeSH
- antigeny sacharidové asociované s nádorem krev MeSH
- dospělí MeSH
- Helicobacter pylori imunologie MeSH
- imunoglobulin G krev MeSH
- infekce vyvolané Helicobacter pylori imunologie MeSH
- karcinoembryonální antigen krev MeSH
- lidé středního věku MeSH
- lidé MeSH
- matrixová metaloproteinasa 7 krev MeSH
- multivariační analýza MeSH
- nádorové biomarkery krev MeSH
- nádory žaludku krev diagnóza MeSH
- pepsinogen A krev MeSH
- protilátky bakteriální krev MeSH
- rizikové faktory MeSH
- senioři nad 80 let MeSH
- senioři MeSH
- teoretické modely * MeSH
- Check Tag
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- senioři nad 80 let MeSH
- senioři MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
Biorelevant dissolution instruments represent an important tool for pharmaceutical research and development. These instruments are designed to simulate the dissolution of drug formulations in conditions most closely mimicking the gastrointestinal tract. In this work, we focused on the optimization of dissolution compartments/vessels for an updated version of the biorelevant dissolution apparatus-Golem v2. We designed eight compartments of uniform size but different inner geometry. The dissolution performance of the compartments was tested using immediate release caffeine tablets and evaluated by standard statistical methods and principal component analysis. Based on two phases of dissolution testing (using 250 and 100 mL of dissolution medium), we selected two compartment types yielding the highest measurement reproducibility. We also confirmed a statistically ssignificant effect of agitation rate and dissolution volume on the extent of drug dissolved and measurement reproducibility.
We have developed a method to longitudinally classify subjects into two or more prognostic groups using longitudinally observed values of markers related to the prognosis. We assume the availability of a training data set where the subjects' allocation into the prognostic group is known. The proposed method proceeds in two steps as described earlier in the literature. First, multivariate linear mixed models are fitted in each prognostic group from the training data set to model the dependence of markers on time and on possibly other covariates. Second, fitted mixed models are used to develop a discrimination rule for future subjects. Our method improves upon existing approaches by relaxing the normality assumption of random effects in the underlying mixed models. Namely, we assume a heteroscedastic multivariate normal mixture for random effects. Inference is performed in the Bayesian framework using the Markov chain Monte Carlo methodology. Software has been written for the proposed method and it is freely available. The methodology is applied to data from the Dutch Primary Biliary Cirrhosis Study.
- MeSH
- biliární cirhóza farmakoterapie MeSH
- biologické markery analýza MeSH
- cholagoga a choleretika terapeutické užití MeSH
- diskriminační analýza MeSH
- interpretace statistických dat MeSH
- kyselina ursodeoxycholová terapeutické užití MeSH
- lidé MeSH
- lineární modely MeSH
- longitudinální studie MeSH
- počítačová simulace MeSH
- progrese nemoci MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
Growing incidence of testicular cancer around the world stimulates research attempting to explain the trends. This study quantified the contribution of different types of potential risk factors for testicular germ-cell cancer (TGCC) with differentiation between seminoma and non-seminoma. A standardized questionnaire containing demographic data, pre- and perinatal factors, social, lifestyle and occupational parameters was prepared. The data file consists of n = 356 TGCCs (seminoma: n = 195; non-seminoma: n = 161) and n = 317 controls, frequency matched on age to cases. The following factors were significantly associated with the risk of TGCCs in univariate analyses (ORs): atrophic testis (5.3), smoking over 12 pack-yr (4.9), cryptorchidism (2.9), testicular trauma (2.0), birth weight under 3,000 g (1.6), low degree of education (3.0) in correlation with manual occupation (2.3) and finally, overall familial cancer history (1.5) and familial history of breast (1.8) and prostate cancer (3.9). On the other hand, maternal age over 20 yr (OR < 0.4) and moderate recreational sport activity (OR = 0.5) significantly reduced the risk of TGCCs. A significant risk was associated with cryptorchidism (OR = 2.9; 95% CI = 1.5 - 5.9) where orchidopexy was delayed after 5 yr of age (OR = 5.2; 95% CI = 1.5-18.1). Delayed orchidopexy was associated namely with the risk of seminomas (OR = 7.5; 95% CI = 2.1-26.7). Only some of the variables were retained in multivariate model for TGCCs as well as for histological subtypes (multivariate adjusted OR for all TGCCs): atrophic testis (5.9), family history of prostate cancer (4.8), cryptorchidism (3.8) and interaction term 'low degree of education & manual occupation' (3.0). Familial history of breast cancer elevated risk of TGCCs and of seminomas (OR: 2.01 - 2.18). Birth weight under 3,000 g was retained in a multivariate model for TGCCs with a borderline significance (OR = 1.67). We could not rule out any type of risk factors, as each one was significantly represented in the final multivariate models. Familial cancer history remained to be an influential risk factor, altogether with some lifestyle and occupational parameters. This suggests that both environmental exposures and genetic inheritance can play role in the moderation of the risk of TGCC.
- MeSH
- dospělí MeSH
- financování organizované MeSH
- kouření MeSH
- lidé středního věku MeSH
- lidé MeSH
- mladiství MeSH
- multivariační analýza MeSH
- rizikové faktory MeSH
- seminom epidemiologie MeSH
- socioekonomické faktory MeSH
- studie případů a kontrol MeSH
- testikulární nádory epidemiologie etiologie genetika MeSH
- Check Tag
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- mladiství MeSH
- mužské pohlaví MeSH
- Geografické názvy
- Česká republika MeSH
... The Markov model makes up an important special case, but it also describes how easily more general models ... ... Frailty models, which are random effects models for survival data, make a second approach; they extend ... ... survival models. ... ... 5.5.4 The Marshall-Olkin model 165 -- 5.5.5 The combined model 166 -- 5.5.6 The alternating state model ... ... 184 -- 6.3.3 Non-parametric models for the disability model 185 -- 6.3.4 Non-parametric models for bivariate ...
Statistics for biology and health
1st ed. xvii, 542 s.
Cross-contamination of eukaryotic cell lines used in biomedical research represents a highly relevant problem. Analysis of repetitive DNA sequences, such as Short Tandem Repeats (STR), or Simple Sequence Repeats (SSR), is a widely accepted, simple, and commercially available technique to authenticate cell lines. However, it provides only qualitative information that depends on the extent of reference databases for interpretation. In this work, we developed and validated a rapid and routinely applicable method for evaluation of cell culture cross-contamination levels based on mass spectrometric fingerprints of intact mammalian cells coupled with artificial neural networks (ANNs). We used human embryonic stem cells (hESCs) contaminated by either mouse embryonic stem cells (mESCs) or mouse embryonic fibroblasts (MEFs) as a model. We determined the contamination level using a mass spectra database of known calibration mixtures that served as training input for an ANN. The ANN was then capable of correct quantification of the level of contamination of hESCs by mESCs or MEFs. We demonstrate that MS analysis, when linked to proper mathematical instruments, is a tangible tool for unraveling and quantifying heterogeneity in cell cultures. The analysis is applicable in routine scenarios for cell authentication and/or cell phenotyping in general.
- MeSH
- analýza hlavních komponent MeSH
- buněčné linie MeSH
- hmotnostní spektrometrie metody MeSH
- kalibrace MeSH
- kokultivační techniky MeSH
- lidé MeSH
- lidské embryonální kmenové buňky fyziologie MeSH
- multivariační analýza MeSH
- myši MeSH
- neuronové sítě * MeSH
- odběr biologického vzorku MeSH
- zvířata MeSH
- Check Tag
- lidé MeSH
- myši MeSH
- zvířata MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
AIM: Current diagnostics of bone metastatic disease is not satisfactory for early detection or regular process monitoring. The combination of biomarkers and the multiparametric approach was described as effective in other oncology diagnoses. The aim of the study was to improve the difference diagnostics between bone-metastatic disease and solid tumors using mutivariate logistic regression model. METHODS: We assessed the group of 131 patients with the following diagnoses: prostate cancer, breast cancer, lung cancer, and colorectal cancer. According to the results of scintigraphy, the cohort was divided into 2 groups based on the occurrence of bone metastases. Group 0 was a control group of 75 patients with no signs of bone metastases and group 1 included 56 patients with bone metastases. RESULTS: We used stepwise selection multivariate logistic regression for choosing the multimarker formula for calculation of risk score for bone metastases diagnostics. For detection of bone metastasis, it was shown to be most effective measurement of 3 biomarkers: procollagen type 1 N-terminal propeptide, growth differentiation factor-15, and osteonectin and combining with calculation of risk score by designating measured concentrations in mathematical formula: bone risk score = procollagen type 1 N-terminal propeptide × 0.0500 + growth differentiation factor-15 × 1.4179 + osteonectin × 0.00555. CONCLUSION: We identified growth differentiation factor-15 as the best individual marker for bone metastasis diagnostics. The best formula for risk score includes levels of 3 biomarkers-procollagen type 1 N-terminal propeptide, growth differentiation factor-15, and osteonectin. The new score has better performance described by higher area under the curve than individual biomarkers. A further study is necessary to confirm these findings incorporating a larger number of patients.
- MeSH
- dospělí MeSH
- kohortové studie MeSH
- kosti a kostní tkáň metabolismus patologie MeSH
- lidé středního věku MeSH
- lidé MeSH
- multivariační analýza MeSH
- nádorové biomarkery metabolismus MeSH
- nádory kostí metabolismus patologie sekundární MeSH
- osteonektin metabolismus MeSH
- radioisotopová scintigrafie metody MeSH
- růstový diferenciační faktor 15 metabolismus MeSH
- senioři nad 80 let MeSH
- senioři MeSH
- Check Tag
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- mužské pohlaví MeSH
- senioři nad 80 let MeSH
- senioři MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
Cíl Klinický průběh onemocnění pacientů s chronickou lymfocytární leukémií (chronic lymphocytic leukemia, CLL) je velmi variabilní; někteří pacienti mají indolentní onemocnění a nevyžadují žádnou léčbu, zatímco jiní mají agresivní onemocnění vyžadující časné léčení. Zahájení terapie se nadále řídí kritérii pro aktivní onemocnění. Provedli jsme mnohorozměrnou analýzu s cílem určit prognostické faktory spojené nezávisle s dobou do první léčby pacientů s CLL. Pacienti a metody V mnohorozměrné analýze byly vyhodnoceny tradiční laboratorní a klinické prognostické faktory a nové prognostické faktory, jimiž jsou např. fluorescenční hybridizace in situ (fluorescent in situ hybridization, FISH), mutační status IGHV a exprese ZAP-70 vyšetřené při první návštěvě v MD Anderson Cancer Center, s dobou do první léčby. Tento mnohorozměrný model byl použit k sestrojení nomogramu – statisticky váženého nástroje pro výpočet 2leté a 4leté pravděpodobnosti zahájení léčby a mediánu doby do prvního léčení. Výsledky Bylo zjištěno 930 dosud neléčených pacientů, kteří podstoupili vyšetření tradičních a nových prognostických faktorů; pacienti, kteří neměli během 3 měsíců po první návštěvě aktivní CLL vyžadující zahájení léčby, byli pozorováni k zjištění doby do prvního léčení. S kratší dobou do prvního léčení byly nezávisle spojeny následující charakteristiky: tři lokalizace postižených lymfatických uzlin, zvětšení cervikálních krčních uzlin, přítomnost delece 17p nebo delece 11q podle FISH, zvýšená koncentrace laktátdehydrogenázy v séru a mutační status IGHV bez mutace. Závěr Vytvořili jsme mnohorozměrný model, jehož součástí jsou tradiční a novější prognostické faktory, k určení pacientů s vysokým rizikem progrese vyžadující léčbu. Tento model by mohl být užitečný k určení pacientů vhodných pro zařazení do studií časných intervencí.
- MeSH
- časové faktory MeSH
- chronická lymfatická leukemie genetika metabolismus terapie MeSH
- delece genu MeSH
- dospělí MeSH
- hodnocení rizik MeSH
- imunohistochemie MeSH
- Kaplanův-Meierův odhad MeSH
- L-laktátdehydrogenasa genetika metabolismus MeSH
- lidé středního věku MeSH
- lidé MeSH
- multivariační analýza MeSH
- mutace MeSH
- nádorové biomarkery metabolismus MeSH
- nomogramy MeSH
- odds ratio MeSH
- prediktivní hodnota testů MeSH
- prognóza MeSH
- proporcionální rizikové modely MeSH
- protein-tyrosinkináza ZAP-70 metabolismus MeSH
- průtoková cytometrie MeSH
- rizikové faktory MeSH
- senioři nad 80 let MeSH
- senioři MeSH
- těžké řetězce imunoglobulinů genetika MeSH
- Check Tag
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- mužské pohlaví MeSH
- senioři nad 80 let MeSH
- senioři MeSH
- ženské pohlaví MeSH
- Publikační typ
- práce podpořená grantem MeSH
- randomizované kontrolované studie MeSH
- Geografické názvy
- Texas MeSH
