Biomedical subjects

Jeremy M G Taylor

Publications and source records attributed to Jeremy M G Taylor.

At least 19 recordsLinked to original sources

PubMed2007

Analysis on binary responses with ordered covariates and missing data.

We consider the situation of two ordered categorical variables and a binary outcome variable, where one or both of the categorical variables may have missing values. The goal is to estimate the probability of response of the outcome variable for each cell of the contingency table of categorical variables while incorporating the fact that the categorical variables are ordered. The probability of response is assumed to change monotonically as each of the categorical variables changes level. A probability model is used in which the response is binomial with parameters p(ij) for each cell (i, j) and the number of observations in each cell is multinomial. Estimation approaches that incorporate Gibbs sampling with order restrictions on p(ij) induced via a prior distribution, two-dimensional isotonic regression and multiple imputation to handle missing values are considered. The methods are compared in a simulation study. Using a fully Bayesian approach with a strong prior distribution to induce ordering can lead to large gains in efficiency, but can also induce bias. Utilizing isotonic regression can lead to modest gains in efficiency, while minimizing bias and guaranteeing that the order constraints are satisfied. A hybrid of isotonic regression and Gibbs sampling appears to work well across a variety of scenarios. The methods are applied to a pancreatic cancer case-control study with two biomarkers.

Algorithms↗

PubMed2007

Multiple imputation for interval censored data with auxiliary variables.

We propose a non-parametric multiple imputation scheme, NPMLE imputation, for the analysis of interval censored survival data. Features of the method are that it converts interval-censored data problems to complete data or right censored data problems to which many standard approaches can be used, and that measures of uncertainty are easily obtained. In addition to the event time of primary interest, there are frequently other auxiliary variables that are associated with the event time. For the goal of estimating the marginal survival distribution, these auxiliary variables may provide some additional information about the event time for the interval censored observations. We extend the imputation methods to incorporate information from auxiliary variables with potentially complex structures. To conduct the imputation, we use a working failure-time proportional hazards model to define an imputing risk set for each censored observation. The imputation schemes consist of using the data in the imputing risk sets to create an exact event time for each interval censored observation. In simulation studies we show that the use of multiple imputation methods can improve the efficiency of estimators and reduce the effect of missing visits when compared to simpler approaches. We apply the approach to cytomegalovirus shedding data from an AIDS clinical trial, in which CD4 count is the auxiliary variable.

CD4 Lymphocyte Count↗

PubMed2006

The impact of dose on parotid salivary recovery in head and neck cancer patients treated with radiation therapy.

PURPOSE: A common side effect experienced by head and neck cancer patients after radiation therapy (RT) is impairment of the parotid glands' ability to produce saliva. Our purpose is to investigate the relationship between radiation dose and saliva changes in the 2 years after treatment. METHODS AND MATERIALS: The study population includes 142 patients treated with conformal or intensity-modulated radiotherapy. Saliva flow rates from 266 parotid glands are measured before and 1, 3, 6, 12, 18, and 24 months after treatment. Measurements are collected separately from each gland under both stimulated and unstimulated conditions. Bayesian nonlinear hierarchical models were developed and fit to the data. RESULTS: Parotids receiving higher radiation produce less saliva. The largest reduction is at 1-3 months after RT followed by gradual recovery. When mean doses are lower (e.g., <25 Gy), the model-predicted average stimulated saliva recovers to pretreatment levels at 12 months and exceeds it at 18 and 24 months. For higher doses (e.g., >30 Gy), the stimulated saliva does not return to original levels after 2 years. Without stimulation, at 24 months, the predicted saliva is 86% of pretreatment levels for 25 Gy and <31% for >40 Gy. We do not find evidence to support that the overproduction of stimulated saliva at 18 and 24 months after low dose in 1 parotid gland is the result of low saliva production from the other parotid gland. CONCLUSIONS: Saliva production is affected significantly by radiation, but with doses <25-30 Gy, recovery is substantial and returns to pretreatment levels 2 years after RT.

Adult↗

PubMed2006

Survival analysis using auxiliary variables via non-parametric multiple imputation.

We develop an approach, based on multiple imputation, that estimates the marginal survival distribution in survival analysis using auxiliary variables to recover information for censored observations. To conduct the imputation, we use two working survival models to define a nearest neighbour imputing risk set. One model is for the event times and the other for the censoring times. Based on the imputing risk set, two non-parametric multiple imputation methods are considered: risk set imputation, and Kaplan-Meier imputation. For both methods a future event or censoring time is imputed for each censored observation. With a categorical auxiliary variable, we show that with a large number of imputes the estimates from the Kaplan-Meier imputation method correspond to the weighted Kaplan-Meier estimator. We also show that the Kaplan-Meier imputation method is robust to mis-specification of either one of the two working models. In a simulation study with time independent and time-dependent auxiliary variables, we compare the multiple imputation approaches with an inverse probability of censoring weighted method. We show that all approaches can reduce bias due to dependent censoring and improve the efficiency. We apply the approaches to AIDS clinical trial data comparing ZDV and placebo, in which CD4 count is the time-dependent auxiliary variable.

Biometry↗

PubMed2006

Gene expression signatures for predicting prognosis of squamous cell and adenocarcinomas of the lung.

Non-small-cell lung cancers (NSCLC) compose 80% of all lung carcinomas with squamous cell carcinomas (SCC) and adenocarcinoma representing the majority of these tumors. Although patients with early-stage NSCLC typically have a better outcome, 35% to 50% will relapse within 5 years after surgical treatment. We have profiled primary squamous cell lung carcinomas from 129 patients using Affymetrix U133A gene chips. Unsupervised analysis revealed two clusters of SCC that had no correlation with tumor stage but had significantly different overall patient survival (P = 0.036). The high-risk cluster was most significantly associated with down-regulation of epidermal development genes. Cox proportional hazard models identified an optimal set of 50 prognostic mRNA transcripts using a 5-fold cross-validation procedure. Quantitative reverse transcription-PCR and immunohistochemistry using tissue microarrays were used to validate individual gene candidates. This signature was tested in an independent set of 36 SCC samples and achieved 84% specificity and 41% sensitivity with an overall predictive accuracy of 68%. Kaplan-Meier analysis showed clear stratification of high-risk and low-risk patients [log-rank P = 0.04; hazard ratio (HR), 2.66; 95% confidence interval (95% CI), 1.01-7.05]. Finally, we combined the SCC classifier with our previously identified adenocarcinoma prognostic signature and showed that the combined classifier had a predictive accuracy of 71% in 72 NSCLC samples also showing significant differences in overall survival (log-rank P = 0.0002; HR, 3.54; 95% CI, 1.74-7.19). This prognostic signature could be used to identify patients with early-stage high-risk NSCLC who might benefit from adjuvant therapy following surgery.

Adenocarcinoma↗

PubMed2006

Racial disparities in resource utilization for cystectomy.

OBJECTIVES: To examine the association of race with mortality and resource use among patients requiring cystectomy for bladder cancer, given the known racial differences with regard to bladder cancer incidence and survival. METHODS: Using the Nationwide Inpatient Sample (a nationally representative data set), 22,088 patients who underwent cystectomy for bladder cancer from 1988 to 2000 were identified using the International Classification of Disease, Ninth Revision, codes. The outcomes included in-hospital mortality, length of stay (LOS), and discharge status. Multivariable models were developed to perform risk-adjusted analyses and identify factors associated with these outcomes. RESULTS: The overall mortality rate after cystectomy was 2.9%. Unadjusted analyses revealed significant racial differences with respect to in-hospital mortality, LOS, and discharge disposition. Whites had a mortality rate of 2.8% compared with 4.2% for blacks and 3.9% for Hispanics (P = 0.006). Whites had a prolonged LOS 24.9% of the time compared with 38.2% for blacks and 24.6% for Hispanics (P < 0.001). The rate at which whites were discharged to subacute care facilities was 9.9% compared with 11.2% for black patients and 7.7% for Hispanics (P < 0.001). After adjusting for confounding factors, blacks were more likely to experience in-hospital mortality and prolonged LOS (odds ratios 1.66 and 2.10, respectively) compared with whites, although no significant differences were observed for Hispanics. No significant racial differences were noted for discharge status after risk adjustment. CONCLUSIONS: Black patients undergoing cystectomy for bladder cancer had greater mortality and greater LOS than did white patients. Additional study using detailed clinical data is necessary to identify the underlying causes of these differences.

Black or African American↗

PubMed2006

Hidden Markov model for defining genomic changes in lung cancer using gene expression data.

The study of gene expression patterns in relationship to chromosomal position, the "transcriptome map," has become an area of active research and has revealed unexpected chromosomal regions within which gene expression levels are highly correlated. In cancer research, these regional changes in gene expression that may result from alterations at the chromosome level such as gene amplification or loss. To facilitate the search for such regions utilizing gene expression data, we have developed a hidden Markov model (HMM). Maximum penalized likelihood is used to estimate the parameters in the model. This method is applied to a lung cancer microarray experiment, including 86 human lung adenocarcinomas. Several regions identified through the HMM are consistent with known recurrent regions of amplification or deletion in this cancer. We further demonstrate the association of these abnormal expression regions with measures of disease status, such as tumor stage, differentiation, and survival. These findings suggest that genes in these regions may play a major role in the process of carcinogenesis of the lung. Our proposed method provides a valuable tool to accurately pinpoint regions of abnormal expression for further investigation.

Adenocarcinoma↗

PubMed2006

A nonlinear model with latent process for cognitive evolution using multivariate longitudinal data.

Cognition is not directly measurable. It is assessed using psychometric tests, which can be viewed as quantitative measures of cognition with error. The aim of this article is to propose a model to describe the evolution in continuous time of unobserved cognition in the elderly and assess the impact of covariates directly on it. The latent cognitive process is defined using a linear mixed model including a Brownian motion and time-dependent covariates. The observed psychometric tests are considered as the results of parameterized nonlinear transformations of the latent cognitive process at discrete occasions. Estimation of the parameters contained both in the transformations and in the linear mixed model is achieved by maximizing the observed likelihood and graphical methods are performed to assess the goodness of fit of the model. The method is applied to data from PAQUID, a French prospective cohort study of ageing.

Aged↗

PubMed2006

Comparing an experimental agent to a standard agent: relative merits of a one-arm or randomized two-arm Phase II design.

BACKGROUND: Phase II clinical trials in cancer are used to assess whether a new agent has sufficiently promising efficacy to proceed on to a larger definitive study comparing the new agent to a standard agent. PURPOSE: A crucial issue in determining the usefulness of a one-arm design is the uncertainty of the historical response rate of the standard therapy. Therefore, we contrast the usual one-arm design of a Phase II trial with a randomized two-arm design that uses the same number of patients. METHODS: We use simulations and analytical approximations to compare the two designs under a range of realistic values for the historical rate uncertainty and a range of treatment effects. We also extend the simulation model to compare the efficiency of the two designs in settings where multiple Phase II studies are used to make decisions about moving on to a Phase III study. RESULTS: For a one-arm design the probability of correctly identifying an effective experimental agent tends to be at least 0.7 in the cases considered, with the corresponding value for a randomized two-arm design within 0.05-0.10 above or below the one-arm design. An increase in total sample size from 30 patients to 80 patients tends to increase the probability of correctly identifying an effective experiment agent more in the two-arm design than the the one-arm design, particularly when the uncertainty in the historical response rate is large. LIMITATIONS: These results for binary response measures are derived from the specific scenarios and assumptions considered in the simulation study and may not apply to situations outside the range considered. CONCLUSIONS: We find that a one-arm design is preferred for small sample sizes, but a two-arm design may be preferred with larger sample sizes or if the uncertainty in the historical response rates is large.

Antineoplastic Agents↗

PubMed2005

CDX2 polymorphisms, RNA expression, and risk of colorectal cancer.

In adult mammals, CDX2 acts as a transcription factor and is expressed in intestinal epithelial cells. Down-regulation of CDX2 is frequently observed in colorectal cancer, suggesting its loss may cause dedifferentiation of gastrointestinal epithelial cells. However, it is not clear whether inherited variants of CDX2 are associated with risk of colorectal cancer. Using epidemiologic data and tumors from a population-based case-control study in Israel, we identified novel single nucleotide polymorphisms (SNPs) by resequencing 35 cases, compared genotype and haplotype frequencies in 455 matched pairs, and characterized the tumor characteristics of all 455 cases by microsatellite instability analysis, in addition to a partially overlapping set of 201 frozen tumors with expression profiling data (82/201) from the same study. Nine polymorphisms were identified in the 35 cases, and none of the SNPs or haplotypes were associated with risk of colorectal cancer in the 455 matched pairs. These variants were not associated with CDX2 expression in the 83 subjects with expression data. We evaluated subject and tumor characteristics in the 201 subjects with CDX2 tumor expression data. Reduced CDX2 expression was associated with tumor location (right sided), poor differentiation, high microsatellite instability status, and a positive first-degree family history. We conclude that it is unlikely that common CDX2 variants account for a measurable fraction of susceptibility to colorectal cancer in this population. However, CDX2 expression levels were strongly associated with microsatellite instability and tumor location in the gastrointestinal tract, consistent with a possible role in the specification of gastrointestinal epithelial cell fate in humans.

Aged↗

PubMed2005

A Bayesian mixture model relating dose to critical organs and functional complication in 3D conformal radiation therapy.

A goal of cancer radiation therapy is to deliver maximum dose to the target tumor while minimizing complications due to irradiation of critical organs. Technological advances in 3D conformal radiation therapy has allowed great strides in realizing this goal; however, complications may still arise. Critical organs may be adjacent to tumors or in the path of the radiation beam. Several mathematical models have been proposed that describe the relationship between dose and observed functional complication; however, only a few published studies have successfully fit these models to data using modern statistical methods which make efficient use of the data. One complication following radiation therapy of head and neck cancers is the patient's inability to produce saliva. Xerostomia (dry mouth) leads to high susceptibility to oral infection and dental caries and is, in general, unpleasant and an annoyance. We present a dose-damage-injury model that subsumes any of the various mathematical models relating dose to damage. The model is a nonlinear, longitudinal mixed effects model where the outcome (saliva flow rate) is modeled as a mixture of a Dirac measure at zero and a gamma distribution whose mean is a function of time and dose. Bayesian methods are used to estimate the relationship between dose delivered to the parotid glands and the observational outcome-saliva flow rate. A summary measure of the dose-damage relationship is modeled and assessed by a Bayesian chi(2) test for goodness-of-fit.

Bayes Theorem↗

PubMed2005

Comparison of seven methods for producing Affymetrix expression scores based on False Discovery Rates in disease profiling data.

BACKGROUND: A critical step in processing oligonucleotide microarray data is combining the information in multiple probes to produce a single number that best captures the expression level of a RNA transcript. Several systematic studies comparing multiple methods for array processing have used tightly controlled calibration data sets as the basis for comparison. Here we compare performances for seven processing methods using two data sets originally collected for disease profiling studies. An emphasis is placed on understanding sensitivity for detecting differentially expressed genes in terms of two key statistical determinants: test statistic variability for non-differentially expressed genes, and test statistic size for truly differentially expressed genes. RESULTS: In the two data sets considered here, up to seven-fold variation across the processing methods was found in the number of genes detected at a given false discovery rate (FDR). The best performing methods called up to 90% of the same genes differentially expressed, had less variable test statistics under randomization, and had a greater number of large test statistics in the experimental data. Poor performance of one method was directly tied to a tendency to produce highly variable test statistic values under randomization. Based on an overall measure of performance, two of the seven methods (Dchip and a trimmed mean approach) are superior in the two data sets considered here. Two other methods (MAS5 and GCRMA-EB) are inferior, while results for the other three methods are mixed. CONCLUSIONS: Choice of processing method has a major impact on differential expression analysis of microarray data. Previously reported performance analyses using tightly controlled calibration data sets are not highly consistent with results reported here using data from human tissue samples. Performance of array processing methods in disease profiling and other realistic biological studies should be given greater consideration when comparing Affymetrix processing methods.

Algorithms↗

PubMed2005

Individualized predictions of disease progression following radiation therapy for prostate cancer.

PURPOSE: Following treatment for localized prostate cancer, men are monitored with serial prostate-specific antigen (PSA) measurements. Refining the predictive value of post-treatment PSA determinations may add to clinical management, and we have developed a model that predicts future PSA values and the time to future clinical recurrence for individual patients. PATIENTS AND METHODS: Data from 934 patients treated between 1987 and 2000 were used to develop a comprehensive statistical model to fit the clinical recurrence events and patterns of PSA data. A logistic model was used for the probability of cure, mixed models were used for serial PSA measurements, and a proportional hazards model was used for recurrences. Data available through February 2001 were fit to the model, and data collected between February 2001 and September 2003 were used for validation. RESULTS: T-stage, baseline PSA, and radiotherapy dosage are all associated with probability of cure. The risk of clinical recurrence in those not cured is strongly affected by the slope of PSA values. We show how the model can be used for individual monitoring of disease progression. For each patient the model predicts, based on baseline characteristics and all post-treatment PSA values, the probability of future clinical recurrences and future PSA values. The model accurately predicts risk of recurrence and future PSA values in the validation data set. CONCLUSION: This predictive information on future PSA values and the risk of clinical relapse for each individual patient, which can be updated with each additional PSA value, may prove useful to patients and physicians in determining post-treatment salvage strategies.

Adult↗

PubMed2005

Interlaboratory comparability study of cancer gene expression analysis using oligonucleotide microarrays.

A key step in bringing gene expression data into clinical practice is the conduct of large studies to confirm preliminary models. The performance of such confirmatory studies and the transition to clinical practice requires that microarray data from different laboratories are comparable and reproducible. We designed a study to assess the comparability of data from four laboratories that will conduct a larger microarray profiling confirmation project in lung adenocarcinomas. To test the feasibility of combining data across laboratories, frozen tumor tissues, cell line pellets, and purified RNA samples were analyzed at each of the four laboratories. Samples of each type and several subsamples from each tumor and each cell line were blinded before being distributed. The laboratories followed a common protocol for all steps of tissue processing, RNA extraction, and microarray analysis using Affymetrix Human Genome U133A arrays. High within-laboratory and between-laboratory correlations were observed on the purified RNA samples, the cell lines, and the frozen tumor tissues. Intraclass correlation within laboratories was only slightly stronger than between laboratories, and the intraclass correlation tended to be weakest for genes expressed at low levels and showing small variation. Finally, hierarchical cluster analysis revealed that the repeated samples clustered together regardless of the laboratory in which the experiments were done. The findings indicate that under properly controlled conditions it is feasible to perform complete tumor microarray analysis, from tissue processing to hybridization and scanning, at multiple independent laboratories for a single study.

Adenocarcinoma↗

PubMed2005

Randomized phase II evaluation of 6 g/m2 of ifosfamide plus doxorubicin and granulocyte colony-stimulating factor (G-CSF) compared with 12 g/m2 of ifosfamide plus doxorubicin and G-CSF in the treatment of poor-prognosis soft tissue sarcoma.

PURPOSE: The relative value of increasing ifosfamide dose in combination chemotherapy for patients with soft tissue sarcoma (STS) is unclear. The purpose of this study was to compare the efficacy and toxicity of doxorubicin with high-dose (HD) ifosfamide or standard-dose (SD) ifosfamide in patients with STS. PATIENTS AND METHODS: Chemotherapy-naive patients with STS were randomly assigned to receive doxorubicin 60 mg/m(2) and either SD ifosfamide (1.5 g/m(2)/d, days 1 through 4) or HD ifosfamide (3.0 g/m(2), days 1 through 4) every 21 days. Patients were stratified by the presence or absence of metastatic disease. End points were overall survival (OS), 1-year disease-free survival (DFS), and toxicity. RESULTS: The study group consisted of 79 patients (52 patients with localized disease and 27 patients with metastases). Both groups were well-balanced with respect to known prognostic factors. There was no significant difference in 1-year DFS comparing SD ifosfamide with HD ifosfamide (55% v 52%; P = .81). For SD ifosfamide, 2- and 3-year OS were 73% and 52% versus 57% and 49% for HD ifosfamide (P = .34). The incidence of grade 3/4 neutropenia, anemia, and thrombocytopenia were 49%, 23%, and 10%, respectively, on the SD ifosfamide arm, compared with 88%, 58%, and 63%, respectively, on the HD ifosfamide arm. There were five early deaths, all on the HD ifosfamide arm. CONCLUSION: When combined with doxorubicin, HD ifosfamide did not improve 1-year DFS and OS. Toxicity was clearly greater with the HD ifosfamide arm, and lack of outcome differences might be explained by toxicities with HD ifosfamide. These results suggest that HD ifosfamide combination regimens should not be used as first-line therapy for patients with STS.

Adolescent↗

PubMed2005

Counterfactual links to the proportion of treatment effect explained by a surrogate marker.

In a randomized clinical trial, a statistic that measures the proportion of treatment effect on the primary clinical outcome that is explained by the treatment effect on a surrogate outcome is a useful concept. We investigate whether a statistic proposed to estimate this proportion can be given a causal interpretation as defined by models of counterfactual variables. For the situation of binary surrogate and outcome variables, two counterfactual models are considered, both of which include the concept of the proportion of the treatment effect, which acts through the surrogate. In general, the statistic does not equal either of the two proportions from the counterfactual models, and can be substantially different. Conditions are given for which the statistic does equal the counterfactual model proportions. A randomized clinical trial with potential surrogate endpoints is undertaken in a scientific context; this context will naturally place constraints on the parameters of the counterfactual model. We conducted a simulation experiment to investigate what impact these constraints had on the relationship between the proportion explained (PE) statistic and the counterfactual model proportions. We found that observable constraints had very little impact on the agreement between the statistic and the counterfactual model proportions, whereas unobservable constraints could lead to more agreement.

Anti-HIV Agents↗

PubMed2004

Melanoma-associated antigens in esophageal adenocarcinoma: identification of novel MAGE-A10 splice variants.

PURPOSE: The melanoma-associated antigens (MAGEs) are tumor-specific antigens recognized by cytotoxic T lymphocytes. In this study, expression of MAGE family A members was evaluated during the development of esophageal adenocarcinoma (EA) as potential targets for immunotherapy. EXPERIMENTAL DESIGN: MAGE-A mRNA expression was evaluated in 46 samples including Barrett's metaplasia (BM), dysplasia, and EA using oligonucleotide microarrays. Expression of MAGE-A proteins was confirmed by immunohistochemistry on tissue microarrays containing 59 EA, 11 dysplasia, and 9 BM samples and by Western blot. To further evaluate MAGE-A10 expression, reverse transcription-polymerase chain reaction (RT-PCR) products were sequenced, and protein expression was determined using a specific antibody. RESULTS: Overexpression of MAGE-A1, MAGE-A2b, MAGE-A3, MAGE-A4, MAGE-A6, MAGE-A9, MAGE-A10, and MAGE-A12 was found in EAs relative to BM on oligonucleotide microarrays. MAGE-A3 overexpression was confirmed by real-time RT-PCR in 21.4% (6 of 28) of esophageal tumors. Immunohistochemistry on tissue microarray revealed MAGE-A proteins in 20.3% (12 of 59) of EAs and MAGE-A10 staining in 16.9% (10 of 59) of EAs. MAGE-A expression was confirmed by Western blot in several esophageal tumors and in two EA cell lines, Flo-1 and Seg-1, whereas Flo-1 also expressed MAGE-A10. Tumors produced from these cell lines in nude mice retained MAGE-A expression. Interestingly, RT-PCR in primary tumors expressing MAGE-A10 protein revealed additional PCR products that were identified as novel MAGE-A10 alternative splice variants using DNA sequencing. CONCLUSIONS: This is the first report of these MAGE-A10 alternative splice sequences, and characterization of MAGE-A expression may provide potential targets for immunotherapy in patients with EA.

Adenocarcinoma↗

PubMed2004

Mitotic rate and younger age are predictors of sentinel lymph node positivity: lessons learned from the generation of a probabilistic model.

BACKGROUND: Sentinel lymph node (SLN) biopsy allows surgeons to identify patients with subclinical nodal involvement who may benefit from lymphadenectomy and, possibly, adjuvant therapy. Several factors have been variably, and sometimes discordantly, reported to have predictive value for SLN metastasis to best select which patients require SLN biopsy. METHODS: We reviewed 419 patients who underwent SLN biopsy for melanoma from a prospectively collected melanoma database. To derive a probabilistic model for the occurrence of a positive SLN, a multivariate logistic model was fit by using a stepwise variable selection method. The accuracy of each model was evaluated by using receiver operator characteristic curves. RESULTS: On univariate analysis, the number of mitoses per square millimeter, increasing Breslow depth, decreasing age, ulceration, and melanoma on the trunk showed a significant relationship to a positive SLN. Multivariate analysis revealed that once age, mitotic rate, and Breslow thickness were included, no other factor, including ulceration, was significantly associated with a positive SLN. The data suggest that younger patients with tumors <1 mm may still have a substantial risk for a positive SLN, especially if the mitotic rate is high. CONCLUSIONS: In addition to Breslow depth, mitoses per square millimeter and younger age were factors identified as independent predictors of a positive SLN. This model may identify patients with thin melanoma at sufficient risk for metastases to justify SLN biopsy.

Adult↗