PubMed Health⌕ Search

SEARCH · PubMed Health

Results for “cluster analysis”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 415 records · Page 23Linked to original sources
PubMed1998

Breast cancer in West Islip, NY: a spatial clustering analysis with covariates.

This paper presents the results of an exploratory spatial analysis of breast cancer clustering in the community of West Islip on Long Island. Using address-level data from a survey of women in West Islip, we analyze the existence and locations of breast cancer clusters among long-term community residents. Statistical and geographical methods are used to first, estimate a logistic regression model of disease as a function of known risk factors and second, analyze spatial clustering among the cases of breast cancer not explained by the modeled risk factors. The method determines the actual locations of clusters so that if there is a potential causal factor in the environment it can be identified for further study. Although little evidence of clustering is uncovered, the methods described here have utility for exploratory spatial analysis in many health contexts.

Adult↗
PubMed2003

[Classification of observer-groups with cluster analysis and the criteria of visual decision for each group].

It is important that the evaluation of X-ray images include the observer's visual characteristics. However, evaluations of X-ray images that include these characteristics are not performed because of the difficulty of quantitatively elucidating visual characteristics. In this study, we classified observers into groups (clusters) by the same criteria of visual decision, using cluster analysis (unweighted Pair-Group method using arithmetic averages), and evaluated X-ray images on the basis of this separation. Clinical application is also discussed. It was found that observer clustering caused a decrease in between-observer variation. Observers were grouped into two different categories: one with the characteristics of radiologists and the other with the characteristics of medical physicists. Our results indicated that the group with the characteristics of radiologists was suitable for the quality control (QC) of X-ray images.

Cluster Analysis↗
PubMed2005

A functional foot type classification with cluster analysis based on plantar pressure distribution during jogging.

The purpose of this study was to establish a reference dataset for peak pressures and pressure-time integrals during jogging, to compare this reference dataset with existing walking data and to develop a foot type classification, all based on plantar pressure data obtained from 215 healthy young adults. The subjects ran at 3.3 m s(-1) over a 16.5 m long running track, with a built-in pressure platform mounted on top of a force platform. Peak pressures, regional impulses and relative regional impulses were measured. These variables were found to be reliable (all intra class correlation coefficients above 0.75) and, except for the heel areas, gender and asymmetry effects could be neglected. Highest peak pressures were found under the heel due to large impact forces during initial contact phase (ICP). In the forefoot, the highest peak pressure was found under the second metatarsal (64.2 +/- 21.1 N cm(-2)). Compared to walking data, overall higher peak pressures and impulses and difference in hallux loading were found during barefoot jogging. Four pressure loading patterns were identified using a K-means cluster analysis, based on the relative regional impulses underneath the forefoot: medial M1 pattern, medial M2 pattern, central pattern and central-lateral pattern. These four pressure loading patterns could help in the functional interpretation of the foot behaviour during the stance phase in slow running.

Adolescent↗
PubMed1999

A cluster analysis of alcohol-related attitudes and behaviors in the general population.

OBJECTIVE: Alcohol use typologies have previously focused on chronic alcohol abusers and alcohol-dependent populations. This empirical typology was created to profile lifestyle patterns associated with nonclinical patterns of alcohol use. METHOD: This study used two surveys sent to a commercial mailback panel, sampled to construct a study population demographically representative of the general U.S. population (N = 2,910). A K-means cluster analysis of alcohol use predictor variables and alcohol use generated the typology. RESULTS: The results suggest five distinct psychobehavioral clusters, referred to by the modal patterns of alcohol use for each cluster: nondrinkers, light drinkers, moderate drinkers, episodic drinkers and regular heavy drinkers. These clusters were found to have predictive validity using related health behaviors, psychosocial variables, personality self-descriptors, and media use as criteria. In particular, moderate drinkers had double the income of any other cluster and showed consistently healthy exercise, cigarette use, and diet patterns as well as a relatively high ranking of health as a personal value. Episodic drinkers had the highest levels of sensation-seeking and drug use and were not health oriented in values and behaviors, although their total weekly consumption was only marginally greater than the moderate drinkers. CONCLUSIONS: The profile of the moderate drinker cluster is consistent with concerns about lifestyle confounds in the relationship between moderate alcohol consumption and cardiovascular health. The episodic drinker profile is consistent with relatively high risk behaviors; this cluster may be a good target for harm-reduction education and intervention efforts.

Adult↗
PubMed1992

Cluster analysis of child behavior checklists of 6 to 11-year-old males with varying degrees of behavior disorders.

Achenbach Child Behavior Checklist ratings were collected on boys aged 6 to 11 years screened as not having significant behavior problems, as clinic-referred boys, and as boys diagnosed as having Attention Deficit-Hyperactivity Disorder alone or together with Oppositional-Defiant Disorder or Conduct Disorder. Cluster analysis resulted in a classification system related to DSM-III-R classification of the boys and parent self-report of mildly antisocial acts. Clusters also enhanced the ability of the instrument to detect Attention Deficit Hyperactivity Disorder and disruptive behavior disorders.

Attention Deficit Disorder with Hyperactivity↗
PubMed2003

Cluster analysis of BOLD fMRI time series in tumors to study the heterogeneity of hemodynamic response to treatment.

BOLD-contrast functional MRI (fMRI) has been used to assess the evolution of tumor oxygenation and blood flow after treatment. The aim of this study was to evaluate K-means-based cluster analysis as a exploratory, data-driven method. The advantage of this approach is that it can be used to extract information without the need for prior knowledge concerning the hemodynamic response function. Two data sets were acquired to illustrate different types of BOLD fMRI response inside tumors: the first set following a respiratory challenge with carbogen, and the second after pharmacological modulation of tumor blood flow using flunarizine. To improve the efficiency of the clustering, a power density spectrum analysis was first used to isolate voxels for which signal changes did not originate from noise or linear drift. The technique presented here can be used to assess hemodynamic response to treatment, and especially to display areas of the tumor with heterogeneous responses.

Animals↗
PubMed2006

BOLD signal and vessel dynamics: a hierarchical cluster analysis.

The aim of the present study was to analyze blood oxygenation level-dependent (BOLD) signal variation during an apnea-based task in order to assess the capability of a functional magnetic resonance imaging (fMRI) procedure to estimate cerebral vascular dynamic effects. We measured BOLD contrast by hierarchical cluster analysis in healthy subjects undergoing an fMRI experiment, in which the task paradigm was one phase of inspirational apnea (IA). By processing the time courses of the fMRI experiment, analysis was performed only on a subclass of all the possible signal patterns; basically, root mean square and absolute variation differences have been calculated. Considering the baseline value obtained by computing the mean value of the initial rest period as reference, particular voxels showed relative important variations during the IA task and during the recovery phase following the IA. We focused our interest on the signal response of voxels that would correspond mainly to white and gray matter regions and that also may be affected by the proximity of large venous vessels. The results are presented as maps of space-temporal distribution of time series variations with two levels of hierarchical clustering among voxels with low to high initial response. Furthermore, we have presented a clustering of the signal response delay, conducting to a partition and identification of specified brain sites.

Blood Vessels↗
PubMed1990

Cluster analysis of an insulin-dependent diabetic cohort towards the definition of clinical subtypes.

Clinical and biochemical data on 111 consecutive insulin-dependent diabetic children enrolled in a longitudinal prospective study were analyzed to determine if more than one clinical expression of Type I diabetes exists. Use of multivariate statistical methods, including Correspondence Analysis, kappa-means clustering and RECPAM (RECursive Partition and AMalgamation), show that there are two well differentiated clinical expressions of IDDM each characterized by a cluster. One is characterized by later age, less severe onset, longer symptom duration, less beta-cell disappearance after 12 months, more females; the other by earlier age, more sudden and severe onset, DR 3/4, earlier disappearance of beta-cell function and more males. RECPAM analysis provides further insight into the structure of the two clusters. An other RECPAM tree identifies low, medium and high risk groups of disappearance of beta-cell function at 12 months after diagnosis.

Adolescent↗
PubMed2003

Cluster analysis of p53 and Ki67 expression, apoptosis, alpha-fetoprotein, and human chorionic gonadotrophin indicates a favorable prognostic subgroup within the embryonal carcinoma germ cell tumor.

PURPOSE: The prognostic information provided by alpha-fetoprotein and human chorionic gonadotrophin in the management of germ cell tumor (GCT) patients is a biochemical reflection of tumor differentiation. Ki67, p53, and apoptosis have been found to be related to proliferation (Ki67), cell death (p53, apoptosis), and possibly differentiation chemoresistance (p53). We sought to determine whether simultaneous expression of one or more of these markers could identify clinically relevant subgroups of patients with nonseminomatous GCT (NSGCT). PATIENTS AND METHODS: These five marker values were obtained for 95 previously untreated patients with embryonal carcinoma with or without other germ cell components. A multivariate cluster analysis was performed to identify patients with similar marker patterns. RESULTS: One prominent cluster (n = 37; 36 testis retroperitoneum), consisting of 26 (70%) good-risk (GR), nine (24%) intermediate-risk (IR), and two (6%) poor-risk (PR) patients, as defined by the International Germ Cell Consensus Cancer Group (IGCCCG), was observed. The 5-year survival of the prominent cluster (with 30% IR/PR patients) was 94% (95% confidence interval [CI], 86% to 100%), which is comparable to the 91% (95% CI, 89% to 93%) 5-year survival of the IGCCCG GR patients. IGCCCG risk status (P =.005) and cluster affiliation (P =.04) were independent predictors of outcome with hazard ratios of 5.0 (95% CI, 1.6 to 15.4) and 4.6 (95% CI, 1.04 to 20.1), respectively. CONCLUSION: These results suggest that there is a subgroup of NSGCT patients with embryonal carcinoma (with or without other histologies) with a specific tumor biology profile (high Ki67, low apoptosis, and low p53) whose survival is better than that of the overall patient group. The unexpectedly good outcome for the prominent cluster and independent-risk status suggest that subgroups of GCT reflecting different abilities to respond to treatment exist within IGCCCG prognostic categories.

Apoptosis↗
PubMed1999

Identification of AD/HD subtypes using laboratory-based measures: a cluster analysis.

The current investigation used laboratory-based measures of inattention, impulsivity, and activity level to identify subgroups of children with attention-deficit/hyperactivity disorder (AD/HD). Data derived from solid state actigraphs and a continuous performance test (CPT) were obtained from a clinically referred sample and submitted to a cluster analysis. These empirically derived groups were then evaluated for clinical relevance and subsequently validated by parent and teacher ratings and tests of intellectual functioning and academic achievement. Four distinct subgroups emerged: Hyperactive-inattentive (HYP-IN), impulsive-inattentive (IMP-IN), inattentive only, and hyperactive only. The HYP-IN group was impaired on measures of intellectual functioning and academic achievement relative to the other three groups. In contrast, the IMP-IN group was generally rated as more aggressive, although this difference was not statistically significant for all measures. The data suggest that the augmentation of clinical descriptors with laboratory-based data may be an effective strategy by which to categorize diagnostic subgroups of AD/HD.

Achievement↗
PubMed2005

Qualitative differences of divalent salts: multidimensional scaling and cluster analysis.

Sensations from salts of iron, calcium, magnesium, and zinc with different anions were studied using a sorting task and multidimensional scaling (MDS). Ten divalent salts were adjusted in concentrations such that the mean intensity ratings were approximately equal. Stimuli were sorted on the basis of similarity to minimize any semantic influence and were examined with and without nasal occlusion to eliminate retronasal cues. Compounds representing the four primary tastes and astringency were also sorted. Similarity estimates were derived from sorting and were submitted to MDS. Divalent salts fell outside the area of the space defined by the four primary tastes. The nose-open condition showed that some of the divalent salts have unique metallic sensations along with astringency. The groupings obtained were corroborated using single-linkage cluster analysis. An iron group was most distinctive in metallic sensations; calcium and magnesium salts were primarily bitter; and zinc salts were characterized by astringency. When nasal cues were not available, the sensations from the divalent salts were mainly explained by bitterness and astringency. Results were consistent with a previous evaluation of divalent salts using descriptive analysis.

Adult↗
PubMed1999

A clinical and pathological study on the characteristics and factors influencing the prognosis of crescentic glomerulonephritis using a cluster analysis.

Crescentic glomerulonephritis (CrGN) is expressed by a rapidly progressive lesion. However, there is no unanimous view on the factors that affect the prognosis. We carried out a follow-up study of 109 CrGN patients consisting of 54 males (age 55.3 +/- 15.7) and 55 females (age 54.0 +/- 16.3) by a cluster analysis using pathomorphological parameters at the time of biopsy, and thus found two categories which were significantly different regarding the speed of progress (P = 0.0249). The component factors of rapidly progressive CrGN included a combination of several factors such as: (i) a high frequency of crescents; (ii) frequent sclerosis and hyalinosis in the glomeruli with crescents; (iii) extensive tubulo-interstitial damage (cellular, fibrocellular and fibrous) in the renal cortex; (iv) hyperproteinuria; (v) high mean blood pressure; and (vi) anemia. Thus, the prognosis of CrGN is regulated by no single factor but instead by a complex combination of mutually associated factors.

Adolescent↗
PubMed1987

Classification of parasuicide by cluster analysis. Types of suicidal behaviour, therapeutic and prognostic implications.

A classification of suicidal behaviour was derived by cluster analysis from descriptive data on parasuicide patients. The grouping was meaningful in terms of clinical interpretation and had both therapeutic and prognostic implications. The sample was broken down into three groups, identified as repeated, serious and non-serious attempts. The repeated attempters had the worst prognosis at 1-year follow-up. When the sample was classified into five groups according to seriousness of the attempts, the repeater and non-serious groups were retained, while the serious attempts were split into three subtypes, which differed on nosological characteristics, treatment disposal and outcome. An excessively high successful suicide rate was found in a small group of elderly attempters.

Behavior↗
PubMed1993

Atypical adenomatous hyperplasia of the lung and its differentiation from adenocarcinoma. Characterization of atypical cells by morphometry and multivariate cluster analysis.

BACKGROUND: Atypical adenomatous hyperplasia (AAH) of the human lung is considered to be an important lesion preceding adenocarcinoma, but its difference from well-differentiated adenocarcinomas is so subtle as to cause diagnostic uncertainty. In view of this, the authors undertook to establish reproducible microscopic criteria for AAH, Type II pneumocyte type, and Clara cell type adenocarcinomas. METHODS: Twelve-parameter morphometry of atypical cells was performed on 97 lesions selected from 303 surgical specimens of lung by routine microscopic examination: all were considered by premorphometry examination to correspond to one of the above three diseases. Measurements were performed on photomicrographs using a digital image analyzer. The data of morphometry were subjected to 12-variate cluster analysis using a mainframe computer. RESULTS: It was demonstrated that the lesions were classifiable into three groups: Cluster 1 (Type II cell adenocarcinoma and AAH), Cluster 2 (AAH), and Cluster 3 (Clara cell adenocarcinoma). Whereas the latter two were created as homogeneous clusters, Cluster 1 was a mixture of Type II tumors and AAH. CONCLUSIONS: AAH in the strict sense of the word is definable by the features of those classified into Cluster 2, with atypia milder than overt adenocarcinomas. These AAH are likely to correspond to one of the steps of carcinogenesis forgoing the final one. The lesions, diagnosed as AAH before morphometry and being assigned to Cluster 1 and therefore not separable from Type II carcinoma, are considered to have been Type II carcinoma from the very beginning, which were however underdiagnosed in routine microscopic examination.

Adenocarcinoma↗
PubMed1994

Deriving non-homogeneous DNA Markov chain models by cluster analysis algorithm minimizing multiple alignment entropy.

Non-homogeneous Markov chain models can represent biologically important regions of DNA sequences. The statistical pattern that is described by these models is usually weak and was found primarily because of strong biological indications. The general method for extracting similar patterns is presented in the current paper. The algorithm incorporates cluster analysis, multiple alignment and entropy minimization. The method was first tested using the set of DNA sequences produced by Markov chain generators. It was shown that artificial gene sequences, which initially have been randomly set up along the multiple alignment panels, are aligned according to the hidden triplet phase. Then the method was applied to real protein-coding sequences and the resulting alignment clearly indicated the triplet phase and produced the parameters of the optimal 3-periodic non-homogeneous Markov chain model. These Markov models were already employed in the GeneMark gene prediction algorithm, which is used in genome sequencing projects. The algorithm can also handle the case in which the sequences to be aligned reveal different statistical patterns, such as Escherichia coli protein-coding sequences belonging to Class II and Class III. The algorithm accepts a random mix of sequences from different classes, and is able to separate them into two groups (clusters), align each cluster separately, and define a non-homogeneous Markov chain model for each sequence cluster.

Algorithms↗
PubMed2003

Cluster analysis of symptoms and health seeking behaviour differentiates subgroups of patients with severe irritable bowel syndrome.

BACKGROUND: Irritable bowel syndrome (IBS) is a heterogeneous condition which is diagnosed according to specific bowel symptom clusters. The aim of the present study was to identify subgroups of IBS subjects using measures of rectal sensitivity and psychological symptoms, in addition to bowel symptoms. Such groupings, which cross conventional diagnostic approaches, may provide greater understanding of the pathogenesis of the condition and its treatment. METHOD: A K means cluster analysis was used to group 107 clinic patients with IBS according to physiological, physical, and psychological parameters. All patients had severe IBS and had failed to respond to usual medical treatment. Twenty nine patients had diarrhoea predominant IBS, 26 constipation predominant, and 52 had an alternating bowel habit. RESULTS: The clusters were most clearly delineated by two variables: "rectal perceptual threshold (volume)" and "number of doctor visits". Three subgroups were formed. Group I comprised patients with low distension thresholds and high rates of psychiatric morbidity, doctor consultations, interpersonal problems, and sexual abuse. Group II also had low distension thresholds but low rates of childhood abuse and moderate levels of psychiatric disorders. Group III had high distension thresholds, constipation or alternating IBS, and low rates of medical consultations and sexual abuse. CONCLUSION: The marked differences across the three groups suggest that each may have a different pathogenesis and respond to different treatment approaches. Inclusion of psychosocial factors in the analysis enabled more clinically meaningful groups to be identified than those traditionally determined by bowel symptoms alone or rectal threshold.

Adult↗
PubMed2005

Clinical profiles of serious suicide attempters consecutively admitted to a university-based hospital: a cluster analysis study.

OBJECTIVE: To verify the presence of different groups of medically serious suicide attempters who had more clinical or surgical seriousness and required admission to a general hospital. METHODS: 121 patients admitted consecutively were assessed. A questionnaire containing items on the patient characteristics and psychometric scales to assess the suicidal intent and lethality were used. A cluster analysis was performed using the K-means method. RESULTS: Three groups were identified: 1) 43 subjects (mostly female) characterized by self-poisoning with medication and low suicidal intent, with highly impulsive suicide attempts; 2) 53 subjects (mostly males) who ingested pesticides and presented both moderate degrees of lethality and suicidal intent; 3) 17 subjects (predominantly males) who used more violent methods and presented high levels of lethality and suicidal intent. CONCLUSIONS: Grouped data of these inpatients could be misleading for follow-up research purposes as our findings indicate that there are relatively distinct clinical profiles among suicide attempters admitted to a general hospital.

Adolescent↗