Map of space-only clusters of non-Hodgkin lymphoma in Denmark.

<p>One area showing statistically significant clustering of non-Hodgkin lymphoma cases (area no. 8), and two areas showing borderline clustering (area no. 9 and 10), based on spatial scan statistics of SaTScan and a maximum cluster size of 10% of the total population, using year when clusters were suggested by Q-statistics. None of these cluster regions were consistently found with both control groups.</p

Map of space-time clusters of non-Hodgkin lymphoma in Denmark adjusted for potential confounding factors.

<p>Three areas showing statistically significant clustering of non-Hodgkin lymphoma cases in Denmark identified with Q-statistics, based on 15 nearest neighbours and adjusted analyses. The circles indicate the extent of the clusters, not the number of cases comprising each cluster. None of these cluster regions were consistently found with both control groups.</p

Results of analyses performed in SaTScan at selected time slices that match the time periods with the most significant space-time clusters found by Q-statistics.

a<p>Indicates at which point in time we decided to apply the methods of SaTScan. ^b Indicates the most significant clusters detected by SaTScan. ^c Number of cases that comprise the most significant clusters detected by SaTScan. ^d Name of the area where SaTScan identified the cluster. ^e Refers to the areas shown on the map in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0060800#pone-0060800-g003" target="_blank">figure 3</a>. ^f Control group.</p

Results of adjusted^a space-time cluster analyses performed in SpaceStat, based on 15 nearest neighbours, 999 permutations, and by three different time scales.

a<p>Adjusted for previous history of autoimmune disease, HIV/AIDS or organ transplantation.</p>b<p>The total number of statistically significant cases with a <i>Q_ik</i> p-value of 0.001, which indicates the number of cases that are centers of clusters over their life-course. ^c Number of statistically significant <i>Q_ik</i> (p  =  0.001) cases that also have significant <i>Q_ikt</i> (p ≤ 0.05) and are members of a cluster of at least 4 cases. ^d Indicate where and when the cases tend to cluster.</p>e<p>Refers to the map in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0060800#pone-0060800-g002" target="_blank">figure 2</a>, which shows the suggested clusters of NHL in Denmark based on the adjusted analyses. ^f Control group.</p

Map of space-time clusters of non-Hodgkin lymphoma in Denmark.

<p>Four areas showing statistically significant clustering of non-Hodgkin lymphoma cases in Denmark identified with Q-statistics, based on 15 nearest neighbours and unadjusted analyses. The circles indicate the extent of the clusters, not the number of cases comprising each cluster. None of these cluster regions were consistently found with both control groups.</p

Results of unadjusted space-time cluster analyses performed in SpaceStat, based on 15 nearest neighbours, 999 permutations, and by three different time scales.

a<p>The total number of statistically significant cases with a <i>Q_ik</i> p-value of 0.001, which indicates the number of cases that are centers of clusters over their life-course. ^b Number of statistically significant <i>Q_ik</i> (p  =  0.001) cases that also have significant <i>Q_ikt</i> (p ≤ 0.05) and are members of a cluster of at least 4 cases. ^c Indicate where and when the cases tend to cluster.</p>d<p>Refers to the map in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0060800#pone-0060800-g001" target="_blank">figure 1</a>, which shows the suggested clusters of NHL in Denmark based on the unadjusted analyses. ^e Control group.</p