Biomedical subjects

Changhong Song

Publications and source records attributed to Changhong Song.

6 recordsLinked to original sources

PubMed2006

Likelihood based tests for spatial randomness.

Many different methods have been proposed to test the spatial randomness of a point pattern adjusting for an inhomogeneous background population. These tests can be classified into cluster detection tests, concerned with the detection and inference of local clusters, and global clustering tests, which collect evidence for clustering throughout the study region. This paper is mainly concerned about global clustering tests. Some tests for spatial randomness are based on likelihoods, which include the spatial and space-time scan statistics with variable window size and Gangnon and Clayton's weighted average likelihood ratio tests. Both of these tests perform well compared to other tests for cluster detection and global clustering, respectively. In this study, we develop other likelihood based tests for global clustering and we explore the use of different weight functions with these tests. The power of these tests is evaluated using simulated data set and compared with existing methods.

Cluster Analysis↗

PubMed2006

Geographically based investigation of prostate cancer mortality in four U.S. Northern Plain states.

BACKGROUND: Historically, prostate cancer mortality rates have been elevated in the U.S. Northern Plains states. The purpose of this study was to investigate possible contributing factors, especially whether there was any association with crop patterns. METHODS: Prostate cancer mortality rates (1950-2000) in four northern plains states (MN, MT, ND, and SD) were compared to rates for 46 other U.S. states. Within the four states, county rates in urban, less urban, and rural areas also were compared. For additional analysis, urban counties and counties with <10% of county area in crops were excluded. The average percent of county area in total cropland 1930-1950 and 1954-1974 was estimated. Using Poisson regression, we investigated whether the average percentage of county area in total cropland, 1930-1950 and 1954-1974, was associated with prostate cancer mortality rates, 1975-2000, respectively. Poisson regression analyses were also used to evaluate associations between rates and major crops, which included spring and durum wheat, winter wheat, corn, and other crops. Population centroids of the Census 2000 block groups were used to estimate the percentage of males aged 35 and older residing in close proximity to small grains crops. RESULTS: Mortality rates were higher in rural compared to urban counties in 1950-2000 (rate ratio [RR]=1.032; 95% CI=1.001-1.063). Rates in 1950-1974 were significantly associated with production of corn and other crops in 1930-1950 (corn: RR per 10% increase=1.033, 95% CI=1.012-1.054; other crops: RR=1.042, 95% CI=1.021-1.063). Mortality rates in 1975-2000 were significantly associated with spring and durum wheat production in 1954-1974 (RR per 10% increase=1.042, 95% CI=1.017-1.067). Prostate cancer mortality rates increased as the percentage of population living within 500 m of small grains crops increased. CONCLUSIONS: Epidemiologic studies to evaluate agricultural practices are warranted to further evaluate the observed associations.

Adult↗

PubMed2006

Cancer map patterns: are they random or not?

BACKGROUND: Maps depicting the geographic variation in cancer incidence, mortality or treatment can be useful tools for developing cancer control and prevention programs, as well as for generating etiologic hypotheses. An important question with every cancer map is whether the geographic pattern seen is due to random fluctuations, as by pure chance there are always some areas with more cases than expected, or whether the map reflects true underlying geographic variation in screening, treatment practices, or etiologic risk factors. METHODS: Nine different tests for spatial randomness are evaluated in very practical settings by applying them to cancer maps for different types of data at different scales of spatial resolution: breast, prostate, and thyroid cancer incidence; breast cancer treatment and prostate cancer stage in Connecticut; and nasopharynx and prostate cancer mortality in the U.S. RESULTS: Tango's MEET, Oden's Ipop, and the spatial scan statistic performed well across all the data sets. Besag-Newell's R, Cuzick-Edwards k-NN, and Turnbull's CEPP often perform well, but the results are highly dependent on the parameter chosen. Moran's I performs poorly for most data sets, whereas Swartz Entropy Test and Whittemore's Test perform well for some data sets but not for other. CONCLUSIONS: When publishing cancer maps we recommend evaluating the spatial patterns observed using Tango's MEET, a global clustering test, and the spatial scan statistic, a cluster detection test.

Adolescent↗

PubMed2006

Targeted versus daily naltrexone: secondary analysis of effects on average daily drinking.

BACKGROUND: To extend our previous findings that naltrexone reduced the likelihood of heavy drinking on a given day among problem drinkers, while targeted administration reduced the likelihood of any drinking, we examined the effects of naltrexone and targeted administration on the continuous outcome of drinks/day. Because treatment response may differ by gender, we also compared the effects on this factor. METHODS: In a double-blind, placebo-controlled study, problem drinkers (n=150, 58% men) were randomly assigned to 8 weeks of treatment with naltrexone (50 mg/day) or placebo, either daily or on a targeted schedule. All subjects also received brief coping skills therapy. To complement the traditional regression analysis conducted previously, a zero-inflated Poisson regression model was used to examine the effects of medication, schedule of administration, and gender on the number of standard drinks consumed daily. RESULTS: Targeted naltrexone, and to a lesser extent targeted placebo, yielded a greater reduction in daily drinking than did daily placebo, an effect that did not differ by gender and that was greater than that seen for daily naltrexone treatment. Relative to daily placebo, daily naltrexone reduced the number of drinks/day only among men, at the level of a nonsignificant trend. CONCLUSIONS: Although in both genders, targeted treatments appeared to reduce the volume of drinking, treatment with targeted naltrexone was somewhat better. In contrast, heavy drinking women showed no benefit from daily naltrexone treatment. Further evaluation of the efficacy of targeted treatments and of daily naltrexone and the relationship of these treatments with gender is warranted.

Adolescent↗

PubMed2005

Tango's maximized excess events test with different weights.

BACKGROUND: Tango's maximized excess events test (MEET) has been shown to have very good statistical power in detecting global disease clustering. A nice feature of this test is that it considers a range of spatial scale parameters, adjusting for the multiple testing. This means that it has good power to detect a wide range of clustering processes. The test depends on the functional form of a weight function, and it is unknown how sensitive the test is to the choice of this weight function and what function provides optimal power for different clustering processes. In this study, we evaluate the performance of the test for a wide range of weight functions. RESULTS: The power varies greatly with different choice of weight. Tango's original choice for the weight function works very well. There are also other weight functions that provide good power. CONCLUSION: We recommend the use of Tango's MEET to test global disease clustering, either with the original weight or one of the alternate weights that have good power.

Journal Article↗

PubMed2003

Power evaluation of disease clustering tests.

BACKGROUND: Many different test statistics have been proposed to test for spatial clustering. Some of these statistics have been widely used in various applications. In this paper, we use an existing collection of 1,220,000 simulated benchmark data, generated under 51 different clustering models, to compare the statistical power of several disease clustering tests. These tests are Besag-Newell's R, Cuzick-Edwards' k-Nearest Neighbors (k-NN), the spatial scan statistic, Tango's Maximized Excess Events Test (MEET), Swartz' entropy test, Whittemore's test, Moran's I and a modification of Moran's I. RESULTS: Except for Moran's I and Whittemore's test, all other tests have good power for detecting some kind of clustering. The spatial scan statistic is good at detecting localized clusters. Tango's MEET is good at detecting global clustering. With appropriate choice of parameter, Besag-Newell's R and Cuzick-Edwards' k-NN also perform well. CONCLUSION: The power varies greatly for different test statistics and alternative clustering models. Consideration of the power is important before we decide which test statistic to use.

Journal Article↗