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Lung cancer mortality among industrial workers exposed to formaldehyde: a Poisson regression analysis of the National Cancer Institute Study.

The Formaldehyde Institute (FI) sponsored additional Poisson regression analysis of lung cancer mortality data from the joint National Cancer Institute (NCI)/FI cohort study of workers exposed to formaldehyde to investigate the previously reported effects of plant and latency period and to assess the impact of short-term workers (under 1 yr employment) on the results. There were 242 lung cancer deaths in this cohort of 20,067 white male workers. With OCMAP software, lung cancer death rates for the white males in this cohort were computed by plant, age, calendar time, and job type for several time-dependent formaldehyde exposures, including formaldehyde exposure in the presence of 12 selected co-exposures: ammonia (AM), antioxidants (AN), asbestos (AS), carbon black (CB), dyes/inks/pigments (DY), hexamethylenetetramine (HX), melamine (ME), particulates (PT), phenol (PH), plasticizers (PL), urea/urea compounds (UR), wood dust (WD), and a composite co-exposure (X5) involving AN, HX, ME, PH, and UR.A 1.6-fold increase in lung cancer risk was found, beginning approximately 16-20 yr after first employment in the study plants with no evidence of a differential effect of latency between hourly and salaried workers or among the various categories of formaldehyde exposure as measured by cumulative average intensity or length of exposure. The statistically significant heterogeneity in lung cancer risk among the 10 plants could not be explained by interplant differences in cumulative or average intensity of exposure to formaldehyde, either without regard to co-exposures or in the presence of any of the 12 co-exposures considered individually. Plant was not a statistically significant predictor of lung cancer risk when cumulative exposure to the composite X5 was included in the model, suggesting that some component of X5, or a correlate, could at least partly account for the overall heterogeneity. No significant associations were found for cumulative, average, or length of exposure to formaldehyde without regard to co-exposure, but positive associations were found for cumulative exposure to formaldehyde in the presence of several co-exposures (AN, HX, ME, PH, and UR). For workers who were never exposed to any of 10 co-exposures associated with an increased lung cancer risk, there was a decreasing pattern of estimated lung cancer risk ratios relative to cumulative formaldehyde exposure. Similar patterns were seen when the analysis was restricted to the long-term workers. Analysis of the internal cohort rates corroborates previous analyses of NCI/FI cohort data in that significant positive associations were found between the risk of lung cancer and cumulative exposure to formaldehyde in the presence of several of the same co-exposures. No such associations were found in the absence of these co-exposures.

Adult↗

The probability of pregnancy after embryo transfer is affected by the age of the patient, cause of infertility, number of embryos transferred and the average morphology score, as revealed by multiple logistic regression analysis.

Because the process of conception is affected by many variables, a multiple logistic regression analysis was performed to assess (i) the impact and relative weight of both patient and embryo variables and (ii) their possible effects on the probability of a vital pregnancy after embryo transfer. A statistical model was constructed predicting the probability of pregnancy after embryo transfer. The variables that contributed significantly to the predictive value of the model were the age of the patient, the cause of infertility, the number of embryos transferred and the average morphology score of the transferred embryos. Embryo variables appeared to have a significant but modest value in predicting the probability of pregnancy after embryo transfer. Other variables, such as the thickness of the endometrium, were found to have no prognostic value. Moreover, we found that their effect could be explained by the variables already included in the model.

Adult↗

Multiple regression analysis of airway responsiveness in adult asthmatic patients.

The aim of this study was to determine which background variables exert the most influence on airway responsiveness in adult asthmatic patients. The relationships between airway response and background variables were investigated by multiple linear and logistic regression analysis in 97 asthmatic patients. Airway responsiveness was measured by the oscillation technique during methacholine inhalation challenge. The regression analyses revealed that modified Aas score "one of asthma severity score", was the major factor contributing to airway hyperreactivity. We conclude that the number of attacks during a previous year is the most important background factor related to airway hyperresponsiveness on a clinical basis.

Asthma↗

An alternative to ecologic regression analysis of mortality rates.

A number of recent papers have used geographically defined data and linear models to study the relationship between a series of epidemiologic factors and the frequency of disease. This "ecologic regression" approach involves serious problems of interpretation. An alternate approach is discussed that does not depend on statistical models, produces easily interpreted results and yields statistical summaries that approximately parallel regression analysis. This alternative procedure is illustrated by using acute lymphocytic leukemia mortality data on a county level from among white females less than five years of age between 1969-1977.

Child, Preschool↗

The influence of anatomical, pathophysiological and other factors on periodontal healing after impacted lower third molar surgery. A multiple regression analysis.

A multifactorial approach has been used to identify some predictors of postoperative intrabony defects (IBD) on the distal surface of the adjacent second molar (M2) after impacted lower third molar (M3) surgery. The material consisted of 215 lower third molar removals, performed on 144 persons (age range 16-53 years; mean 27.2 years). The postoperative examination took place 2 years after impaction surgery and included both clinical and radiographic variables. Statistically significant (5% significance level) predictors of IBD found in stepwise multiple regression analyses were: (1) preoperative intrabony defect M2 distal; (2) age at the time of surgery; (3) size of contact-area M3/M2; (4) root resorption M2 distal; (5) probing dept distal surface of adjacent first molar postoperatively; (6) pathological follicle M3. The regression model with IBD as regressand produced a total R2 of 0.45. When the regressand was the difference between IBD and the preoperative intrabony defect, the regression analysis explained 62% of the variance (R2 = 0.62). These regression models explained the variance in terms of the size of the remaining postoperative intrabony defect as well as in terms of periodontal healing after impacted lower third molar surgery.

Adolescent↗

A multivariate logistic regression analysis in predicting malignancy for patients with ovarian tumors.

OBJECTIVE: Our objective was to improve the preoperative diagnosis of ovarian malignancy using a multivariate logistic regression analysis on the basis of demographic, serologic, gray-scale morphological, and Doppler variables. METHODS: One hundred seventy-one patients with ovarian tumors (120 benign, 51 malignant including 9 tumors of low malignant potential) were studied with transvaginal B-mode, color, and pulsed Doppler ultrasonography before surgery. Based on the gray-scale ultrasound imaging, each tumor was classified as a unilocular cyst, multilocular cyst, unilocular cyst with solid parts, multilocular cyst with solid parts, or solid tumor. Intratumoral blood flow velocity waveforms were recorded on all tumors except unilocular cyst and were evaluated for resistance index (RI) and peak systolic velocity (PSV). Serum CA 125 levels were also measured. RESULTS: Twenty tumors were unilocular cysts and were all benign. Seventy tumors including all unilocular cysts which showed no flows were all benign. The remaining 101 tumors (50 benign, 51 malignant including 9 tumors of low malignant potential) presented intratumoral blood flows. Univariate and multivariate logistic regression analyses were conducted to identify variables predictive of ovarian malignancy in these 101 tumors. The variables included age, menstrual state, serum CA 125 levels, B-mode classification, RI, and PSV. In univariate analysis, menopause, the positivity of CA 125 (> or = 35 U/ml), and PSV larger than or equal to 10.4 cm/s were found to be significantly associated with malignant tumors. The PSV value of 10.4 cm/s was the median in benign tumors. Multivariate analysis showed that serum CA 125 levels (> or = 35 U/ml) (P = 0.002) and PSV (> or = 10.4 cm/s) (P < 0.001) were to be independent predictors of malignancy. CONCLUSION: These results suggest that intratumoral PSV is the strongest means of differentiating benign from malignant ovarian tumors with suspicious gray-scale ultrasonographic findings.

Adolescent↗

Prognostic parameters in myelodysplastic syndromes: a multiple regression analysis.

The influence on survival of 21 basic clinical and hematologic parameters was evaluated in 72 patients with previously untreated myelodysplastic syndromes (MDS). Only five parameters were significant by both survival curves and multiple regression analyses: hemoglobin level, bone marrow (BM) cellularity (estimated from trephine BM biopsies), BM blast percentage, age and BM erythro/myeloid (E/M) ratio. Using these parameters, multiple regression analysis enabled us to predict 34% of the survival of all MDS patients (p less than 0.002), 38% of that of patients who had stable disease (p less than 0.04) and over 80% of that of patients who developed acute leukemia (p less than 0.02). High BM cellularity was the most predictive factor for the development of leukemia. No factor was predictive for patients who died of cytopenic or other complications.

Humans↗

Prediction in medicine by integrating regression trees into regression analysis with optimal scaling.

OBJECTIVES: A new data-analysis strategy is proposed to solve the problems of selecting interaction terms in linear regression on the one hand, and of statistically testing the significance of regression trees on the other hand. METHODS: The proposed strategy combines two data mining techniques: regression trees and regression analysis with optimal scaling (CATREG). The method traces small regression trees using the bootstrap and integrates the results as interaction variables (called "trunk variables") into CATREG. RESULTS: An application to data from cardiac patients shows a relative increase of 19% variance accounted for (16% cross-validated variance), by the CATREG model including the trunk variables compared to the model excluding these variables. CONCLUSIONS: This study indicates that trunk variables can be useful to model interaction effects in prediction problems.

Artificial Intelligence↗

Prognostic factors in childhood asthma: a logistic regression analysis.

Thirty-two factors related to childhood asthma were studied in 200 asthmatic children. Remission of asthma was defined as a period of at least 2 years free of asthma while receiving no treatment. Univariate analysis showed significant associations between persistence of asthma and perennial symptoms with an odds ratio (OR) of 2.5 (95% confidence intervals 1.2 to 5.5); sensitization to house dust mites OR 3.5 (1.2 to 9.6); sensitization to molds, OR 7.9 (2.9 to 21.6); sensitization to pollen, OR 4.8 (1.4 to 16.3); and sensitization to milk protein, OR 5.4 (1.8 to 15.9). There was a positive association of remission of asthma with good treatment compliance, OR 12.1 (1.6 to 91.6). A stepwise logistic regression analysis selected the variables: perennial symptoms (S: 0 = no, 1 = yes), length of follow-up time (T: number of months), treatment compliance (C: 0 = poor, 1 = good), sensitization to fungi (F: 0 to 4), and sensitization to milk protein (M: 0 to 4). The analysis yielded the following formula for calculation of probability of asthma remission P(R): [formula: see text] where S indicates perennial symptoms; T, follow-up time in months; C, compliance; F, allergy to fungi; and M, allergy to milk.

Adolescent↗

Bile acid composition affecting cholesterol dissolution rate: a use of multiple regression analysis.

The dissolution rate of cholesterol in human gallbladder bile was measured by a rotating-disk method using 14C-labeled cholesterol, and was compared with concentrations of the biliary lipids. Computed multiple regression analysis of the results showed that the dissolution rate of cholesterol could be presented as a function of the concentrations of deoxycholic and chenodeoxycholic acid (multiple correlation 0.905; F-value 51.8 (p less than 0.001)). To examine the effect of different kinds of bile acids on cholesterol solubilization, the cholesterol solubility in a gallbladder bile with addition of a conjugated bile acid was determined. Greater solubilization of cholesterol was observed in the bile with addition of sodium deoxycholylglycine and chenodeoxycholylglycine than that with addition of sodium cholylglycine. There was no additional enhancement of the solubility with addition of sodium ursodeoxycholylglycine. These results suggest that the cholelitholytic effect of chenodeoxycholic acid may be greater than that of ursodeoxycholic acid, since the administration of chenodeoxycholic or ursodeoxycholic acid to patients with cholesterol gallstones induced different alterations of biliary bile acid composition.

Bile Acids and Salts↗

Respiratory infections and their influence on lung function in children: a multiple regression analysis.

The relationship between a history of respiratory infections (and associated variables) in children and lung function in later life was examined in a study among 228 children aged 7 to 11 years. In a multiple regression analysis only a few variables showed marked and consistent effects on lung function. Respiratory tract infections showed increasing impairment of lung function with repeated infections, but the impairment was smaller than that caused by current asthma.

Asthma↗

Does regression analysis of lung function data obtained from occupational epidemiologic studies lead to misleading inferences regarding the true effect of smoking?

Exposure-response studies of the relationship between ventilatory function and dust exposure in workers are often quantified using linear regression methods. In coal miners, this technique has indicated that average effects of smoking and moderate dust exposure are roughly equivalent. However, the validity of direct comparison of the average effects of smoking and dust exposure has been questioned, the argument being that smoking causes severe effects in a minority, but leaves the remainder largely unaffected. This hypothesis was studied by examining distributions of FEV1 in a group of working coal miners where mean effects associated with both smoking and dust exposure have been detected. Overall, the results suggest that comparison of average effects of smoking and dust exposure derived from linear regression analysis is valid and not misleading.

Adult↗

Diplotype trend regression analysis of the ADH gene cluster and the ALDH2 gene: multiple significant associations with alcohol dependence.

The set of alcohol-metabolizing enzymes has considerable genetic and functional complexity. The relationships between some alcohol dehydrogenase (ADH) and aldehyde dehydrogenase (ALDH) genes and alcohol dependence (AD) have long been studied in many populations, but not comprehensively. In the present study, we genotyped 16 markers within the ADH gene cluster (including the ADH1A, ADH1B, ADH1C, ADH5, ADH6, and ADH7 genes), 4 markers within the ALDH2 gene, and 38 unlinked ancestry-informative markers in a case-control sample of 801 individuals. Associations between markers and disease were analyzed by a Hardy-Weinberg equilibrium (HWE) test, a conventional case-control comparison, a structured association analysis, and a novel diplotype trend regression (DTR) analysis. Finally, the disease alleles were fine mapped by a Hardy-Weinberg disequilibrium (HWD) measure (J). All markers were found to be in HWE in controls, but some markers showed HWD in cases. Genotypes of many markers were associated with AD. DTR analysis showed that ADH5 genotypes and diplotypes of ADH1A, ADH1B, ADH7, and ALDH2 were associated with AD in European Americans and/or African Americans. The risk-influencing alleles were fine mapped from among the markers studied and were found to coincide with some well-known functional variants. We demonstrated that DTR was more powerful than many other conventional association methods. We also found that several ADH genes and the ALDH2 gene were susceptibility loci for AD, and the associations were best explained by several independent risk genes.

Adult↗

Some capabilities and limitations of multiple regression analysis: application to canine coronary blood flow.

Changes in inspired oxygen and carbon dioxide concentration produced concurrent changes in systemic and coronary haemodynamics in 39 anaesthetized dogs. These changes provided the data base for an exercise in multiple regression analysis using SPSS packages. The physiological problem was to identify influences on coronary blood flow additional to those associated with cardiac work or oxygen consumption. Such influences were identifiable to an extent which was probably limited as much by experimental design as by the underlying physiology. Multiple regression relationships described the integrated response of coronary blood flow to the experimental challenge more completely than any univariate approach. The exercise provided useful insights into a multifactorial problem and the need for deliberate experimental design in attempting to answer specific physiological questions.

Acid-Base Equilibrium↗

Relation of pooled logistic regression to time dependent Cox regression analysis: the Framingham Heart Study.

A standard analysis of the Framingham Heart Study data is a generalized person-years approach in which risk factors or covariates are measured every two years with a follow-up between these measurement times to observe the occurrence of events such as cardiovascular disease. Observations over multiple intervals are pooled into a single sample and a logistic regression is employed to relate the risk factors to the occurrence of the event. We show that this pooled logistic regression is close to the time dependent covariate Cox regression analysis. Numerical examples covering a variety of sample sizes and proportions of events display the closeness of this relationship in situations typical of the Framingham Study. A proof of the relationship and the necessary conditions are given in the Appendix.

Adult↗

Multivariate spectral calibration technique based on regression analysis for the quantitative multiresolution of a ternary mixture containing paracetamol, ascorbic acid and acetylsalicylic acid in effervescent tablets.

Multivariate spectral calibration techniques based on regression analysis were established for the quantitative multiresolution of a ternary mixture containing parecetamol (PAR) ascorbic acid (AA) and acetylsalicylic acid (ASP) having closely overlapping spectra. The mathematical algorithms of multivariate spectral calibrations as namely tri-linear regression calibration (TLRC) and multi-linear regression calibration (MLRC) are based on the use of the linear regression equations at a three-wavelength set and a ten-wavelength set in the range of 215-305 nm. These calibration techniques do not require any chemical pre-treatment and a graphical procedure of the overlapping spectra. The mathematical content of TLRC and MLRC approaches were briefly formulated for the quantitative analysis of three- or multi-component mixtures. The applicability of the formulated calibration models were tested by analysing the various synthetic ternary mixtures consisting of these active compounds and then these models were applied to real pharmaceutical formulations. It was observed that TLRC and MLRC models give a successful quantitative multiresolution. The experimental results of these techniques were compared with each other as well as with those obtained by literature methods.

Acetaminophen↗

Inferring genetic networks from DNA microarray data by multiple regression analysis.

Inferring gene regulatory networks by differential equations from the time series data of a DNA microarray is one of the most challenging tasks in the post-genomic era. However, there have been no studies actually inferring gene regulatory networks by differential equations from genome-level data. The reason for this is that the number of parameters in the equations exceeds the number of measured time points. We here succeeded in executing the inference, not by directly determining parameters but by applying multiple regression analysis to our equations. We derived our differential equations and steady state equations from the rate equations of transcriptional reactions in an organism. Verification with a number of genes related to respiration indicated the validity and effectiveness of our method. Moreover, the steady state equations were more appropriate than the differential equations for the microarray data used.

Computational Biology↗

[Multiple regression analysis of pre- and intra-operative factors in relation to post-operative liver and renal functions].

We investigated the factors which may influence post-operative liver and renal function using a multiple regression analysis after isoflurane or sevoflurane anesthesia in 844 patients (ASA I or II, age 20-90 yr). Hepatic and renal surgeries were excluded from this study. The parameters examined were sex, age, degree of obesity, preoperative liver function, preoperative renal function, infection with hepatitis B or hepatitis C virus, inhalation anesthetics used, MAC.h of anesthesia, the duration of operation, blood loss, amount of blood transfusion, urine volume during operation, and surgical site. Serum GOT, GPT, total bilirubin, BUN and serum creatinine were examined on the 3rd and 7th day after surgery. An increase in serum GOT, GPT or bilirubin was observed for each of the following parameters; male, infection with hepatitis C virus, long operation, and upper abdominal surgery. Postoperative BUN and serum creatinine increased in patients with preoperative renal dysfunction, in elderly patients, and in hepatitis C carriers.

Adult↗