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Figure 1.
Pityriasis rosea data transformation and 3-cluster regression function.

Pityriasis rosea data transformation and 3-cluster regression function.

Figure 2.
Scabies data transformation and 1-cluster regression function.

Scabies data transformation and 1-cluster regression function.

Epidemiologic Studies of Pityriasis Rosea
Epidemiologic Studies of Pityriasis Rosea
1.
Drago  FRanieri  EMalaguti  FLosi  ERebora  A Human herpesvirus 7 in pityriasis rosea. Lancet. 1997;3491367- 1368Article
2.
Drago  FRanieri  EMalaguti  FBattifoglio  MLLosi  ERebora  A Human herpesvirus 7 in patients with pityriasis rosea: electron microscopy investigations and polymerase chain reaction in mononuclear cells, plasma and skin. Dermatology. 1997;195374- 378Article
3.
Watanabe  TSugaya  MNakamura  KTamaki  K Human herpesvirus 7 and pityriasis rosea. J Invest Dermatol. 1999;113288- 289Article
4.
Kempf  WAdams  VKleinhans  M  et al.  Pityriasis rosea is not associated with human herpesvirus 7. Arch Dermatol. 1999;1351070- 1072Article
5.
Yoshida  M Detection of human herpesvirus 7 in patients with pityriasis rosea and healthy individuals [letter]. Dermatology. 1999;199197- 198Article
6.
Kosuge  HTanaka-Taya  KMiyoshi  H  et al.  Epidemiological study of human herpesvirus-6 and human herpesvirus-7 in pityriasis rosea. Br J Dermatol. 2000;143795- 798Article
7.
Offidani  APritelli  ESimonetti  OCellini  AGiornetta  LBossi  G Pityriasis rosea associated with herpesvirus 7 DNA. J Eur Acad Dermatol Venereol. 2000;14313- 314Article
8.
Wong  WRTsai  CYShih  SRChan  HL Association of pityriasis rosea with human herpesvirus-6 and human herpesvirus-7 in Taipei. J Formos Med Assoc. 2001;100478- 483
9.
Chuh  AAPeiris  JS Lack of evidence of active human herpesvirus 7 (HHV-7) infection in three cases of pityriasis rosea in children. Pediatr Dermatol. 2001;18381- 383Article
10.
Chuh  AAChiu  SSPeiris  JS Human herpesvirus 6 and 7 DNA in peripheral blood leucocytes and plasma in patients with pityriasis rosea by polymerase chain reaction: a prospective case control study. Acta Derm Venereol. 2001;81289- 290Article
11.
Chuh  AAChan  HH Prospective case-control study of chlamydia, legionella and mycoplasma infections in patients with pityriasis rosea. Eur J Dermatol. 2002;12170- 173
12.
Sharma  PKYadav  TPGautam  RKTaneja  NSatyanarayana  L Erythromycin in pityriasis rosea: a double-blind, placebo-controlled clinical trial. J Am Acad Dermatol. 2000;42 (2, pt 1) 241- 244Article
13.
Bosc  F Is pityriasis rosea infectious? Lancet. 1981;1662Article
14.
Not Available, Case clustering in pityriasis rosea: support for role of an infective agent. Br Med J (Clin Res Ed). 1982;2841478
15.
Halkier-Sorensen  L Recurrent pityriasis rosea: new episodes every year for five years: a case report. Acta Derm Venereol. 1990;70179- 180
16.
Bjornberg  AHellgren  L Pityriasis rosea: a statistical, clinical and laboratory investigation of 826 patients and matched healthy controls. Acta Derm Venereol. 1962;4250
17.
Chuang  TYPerry  HOIlstrup  DMKurland  LT Recent upper respiratory tract infection and pityriasis rosea: a case-control study of 249 matched pairs. Br J Dermatol. 1983;108587- 591Article
18.
Traore  AKorsaga-Some  NNiamba  PBarro  FSanou  IDrabo  YJ Pityriasis rosea in secondary schools in Ouagadougou, Burkina Faso [in French]. Ann Dermatol Venereol. 2001;128605- 609
19.
Vigh  G Observations on pityriasis rosea patients [in German]. Z Hautkr. 1983;581268- 1272
20.
McPherson  AMcPherson  KRyan  T Is pityriasis rosea an infectious disease? Lancet. 1980;21077Article
21.
Alexander  FEBoyle  PCarli  PM  et al.  Spatial temporal patterns in childhood leukaemia: further evidence for an infectious origin: EUROCLUS project. Br J Cancer. 1998;77812- 817Article
22.
Nakamura  YYanagawa  IKawasaki  T Temporal and geographical clustering of Kawasaki disease in Japan. Prog Clin Biol Res. 1987;25019- 32
23.
Messenger  AGKnox  EGSummerly  RMuston  HLIlderton  E Case clustering in pityriasis rosea: support for role of an infective agent. BMJ (Clin Res Ed). 1982;284371- 373Article
24.
Cameron  DJones  IG Case clustering in pityriasis rosea: support for role of an infective agent [letter]. Br Med J (Clin Res Ed). 1982;2841478Article
25.
Cheong  WKWong  KS An epidemiological study of pityriasis rosea in Middle Road Hospital. Singapore Med J. 1989;3060- 62
26.
Ederer  FMyers  MHMantel  N A statistical problem in space and time: do leukemia cases come in clusters? Biometrics. 1964;20626- 638Article
27.
Naus  JI The distribution of the size of the maximum cluster of points on a line. J Am Stat Assoc. 1965;60532- 538Article
28.
Kulldorff  MNagarwalla  N Spatial disease clusters: detection and inference. Stat Med. 1995;14799- 810Article
29.
Larsen  RJHolmes  CLHeath  CW  Jr A statistical test for measuring unimodal clustering: a description of the test and of its application to cases of acute leukemia in metropolitan Atlanta, Georgia. Biometrics. 1973;29301- 309Article
30.
Molinari  NBonaldi  CDaures  JP Multiple temporal cluster detection. Biometrics. 2001;57577- 583Article
31.
Knox  G Secular pattern of congenital oesophageal atresia. Br J Prev Soc Med. 1959;13222- 226
32.
Berthier  FBoulay  FMolinari  NDaures  JPBlaive  B Rôle de la température sur l'existence de macro agrégats hivernaux d'hémoptysies. Rev Mal Respir. 2000;17 (suppl) 1S125
33.
Chuh  AAT Diagnostic criteria for pityriasis rosea—a prospective case control study for assessment of validity. J Eur Acad Dermatol Venereol. 2003;17101- 103Article
34.
Akaike  H Information theory and an extension of the maximum likelihood principle. Petrov  BNCsaki  Feds.2nd International Symposium on Information Theory Budapest, Hungary Akademiai Kiado Budapest1973;267- 281
35.
Vollum  DI Pityriasis rosea in the African. Trans St Johns Hosp Dermatol Soc. 1973;59269- 271
36.
Jacyk  WK Pityriasis rosea in Nigerians. Int J Dermatol. 1980;19397- 399Article
37.
Chuang  TYIlstrup  DMPerry  HOKurland  LT Pityriasis rosea in Rochester, Minnesota, 1969 to 1978. J Am Acad Dermatol. 1982;780- 89Article
38.
de Souza Sittart  JATayah  MSoares  Z Incidence pityriasis rosea of Gibert in the Dermatology Service of the Hospital do Servidor Publico in the state of São Paulo [in Portuguese]. Med Cutan Ibero Lat Am. 1984;12336- 338
39.
Ahmed  MA Pityriasis rosea in the Sudan. Int J Dermatol. 1986;25184- 185Article
40.
Olumide  Y Pityriasis rosea in Lagos. Int J Dermatol. 1987;26234- 236Article
41.
Harman  MAytekin  SAkdeniz  SInaloz  HS An epidemiological study of pityriasis rosea in the Eastern Anatolia. Eur J Epidemiol. 1998;14495- 497Article
42.
Nanda  AAl-Hasawi  FAlsaleh  QA A prospective survey of pediatric dermatology clinic patients in Kuwait: an analysis of 10,000 cases. Pediatr Dermatol. 1999;166- 11Article
43.
Tay  YKGoh  CL One-year review of pityriasis rosea at the National Skin Centre, Singapore. Ann Acad Med Singapore. 1999;28829- 831
44.
Chuh  AAAu  TS Pityriasis rosea—a review of the specific treatments. Proc R Coll Physicians Edinb. 2001;31203- 207
45.
Palmer  SRCaul  EODonald  DEKwantes  WTillett  H An outbreak of shingles? Lancet. 1985;21108- 1111Article
46.
Hill  AB The environment and disease: association or causation? Proc R Soc Med. 1965;58295- 300
Study
April 2003

Case Clustering in Pityriasis RoseaA Multicenter Epidemiologic Study in Primary Care Settings in Hong Kong

Author Affiliations

From the Department of Medicine, University of Hong Kong (Dr Chuh); Department of Community and Family Medicine, Chinese University of Hong Kong (Dr Lee); and Department of Biostatistics, Institut Universitaire de Recherche Clinique, University of Montpellier I, Montpellier, France (Dr Molinari). The authors have no relevant financial interest in this article.

Arch Dermatol. 2003;139(4):489-493. doi:10.1001/archderm.139.4.489
Abstract

Objectives  To investigate the epidemiology of pityriasis rosea in primary care settings in Hong Kong and to analyze for temporal clustering.

Design  Retrospective epidemiologic study.

Setting  Six primary care teaching practices affiliated with a university.

Patients  Forty-one patients with pityriasis rosea, 564 patients with atopic dermatitis (negative control condition), and 35 patients with scabies (positive control condition).

Methods  We retrieved all records of patients with pityriasis rosea, atopic dermatitis, or scabies diagnosed in 3 years. We analyzed temporal clustering by a method based on a regression model.

Results  The monthly incidence of pityriasis rosea is negatively but insignificantly correlated with mean air temperature (γs = −0.41, P = .19) and mean total rainfall (γs = −0.34, P = .27). Three statistically significant clusters with 7, 6, and 7 cases were identified (P = .03), occurring in the second coldest month in the year (February), the second hottest month (July), and a temperate month (April), respectively. For atopic dermatitis (negative control condition), the nonclustering regression model was selected by Akaike information criteria. For scabies (positive control condition), 1 cluster of 20 cases was detected (P = .03).

Conclusions  Significant temporal clustering independent of seasonal variation occurred in our series of patients with pityriasis rosea. This may be indicative of an infectious cause.

THE CAUSE OF pityriasis rosea (PR) is unknown. Drago et al1,2 reported the association of PR with human herpesvirus 7 infection. Other investigators, however, have described conflicting results.38 Our group previously reported the lack of evidence of active human herpesvirus 7 infection in children9 and adults10 with PR. We also reported the absence of active infection by Chlamydia pneumoniae, Chlamydia trachomatis, Legionella longbeachae, Legionella micdadei, Legionella pneumophila, and Mycoplasma pneumoniae in patients with PR.11

However, evidence supporting an infectious cause of PR is still emerging. A double-blind placebo-controlled study12 reported benefit of erythromycin in modifying the course of PR. Ninety patients with PR were alternately assigned to treatment and placebo groups; 33 (73%) of the 45 patients in the treatment group achieved complete response after 2 weeks of treatment, while none did so in the control group (P<.001).

There have been many case reports of 2 or more patients with PR in the same family or intimate environment.1316 Epidemiologic studies reported associations of PR with history of respiratory tract infections17 and unfavorable social and economic background,18 and higher incidence among workers in larger collectives.19 McPherson et al20 reported that significantly more dermatologists than otolaryngologists had had PR, claiming that frequent exposure to PR by dermatologists during their practice led to an increased risk.

Cluster analysis is an epidemiologic approach to investigate a possible infectious cause and has been applied in diseases including childhood leukemia21 and Kawasaki disease.22 Only 1 study has investigated clustering in PR. Messenger et al23 in 1982 reported significant spatial-temporal clustering in female patients with PR in primary care settings, but not among male patients. They also adopted a "moving window" test and reported a temporal cluster of 16 cases within a 28-day period. It has been criticized that the degree of clustering found may not be valid to support an infectious hypothesis.24 No control was analyzed to establish the validity of their methodology. The effect of seasonal variation was not analyzed. Messenger et al suspected that the prospective nature of their study might have led to enthusiasm of participating general practitioners in reporting the cluster.23 Another prospective study in PR also found such reporting bias.25 In this regard, a retrospective study may paradoxically be better, as such reporting bias is absent.

Different approaches to test temporal clustering are possible. The test statistic of the cell-occupancy approach26 is the number of cases occurring in a subinterval. This method needs to divide the time period into disjointed subintervals arbitrarily. For the scan test,27 the test statistic, the maximum number of cases observed in an interval of a given length t, is found by scaling all intervals of length t in the time. For the scan test with variable window,28 the cluster time window size does not need to be chosen a priori. This test only considers clusters with 5 or more events. With the rank-order procedure,29 the time is divided into subintervals. The test statistic is the sum of the absolute differences between the rank of the subinterval in which a case occurs and the median subinterval rank. This test is sensitive only to unimodal clustering and cannot distinguish between multiple clusters and randomness.

We report here a multicenter retrospective study conducted in primary care settings. Atopic dermatitis and scabies were analyzed concomitantly as control conditions. Atopic dermatitis was chosen as a negative control condition, as it is common, easily diagnosed by family physicians, and clearly known to be noninfectious (although it can be exacerbated by infections). Scabies was selected as a positive control condition, as it is common, easily diagnosed by family physicians, and clearly known to be infectious. Any valid methodology to analyze temporal clustering would be expected to identify nonclustering for the negative control condition and presence of clustering for the positive control condition. Climate data were also analyzed to evaluate the effect of seasonal variation.

The method used in our present study30 does not impose a division of the time. This approach determines time windows with excess events. For any position of the window, it scans continuously across the period of observation. The method is effective with multiple clusters, and the existence of 1 or more clusters is determined by using bootstrapped simulations, which allow us to increase the robustness of the test. The validity of this method has been established by applying it to the classic Knox data set31 and 62 spontaneous admissions for hemoptysis at Nice Hospital in Nice, France.32

The objectives of this study were to investigate the epidemiology of PR in primary care settings in Hong Kong and to analyze for temporal clustering.

METHODS

All affiliated primary care teaching practices with computerized record retrieval systems whose principals agreed to have their records searched were invited to participate. We searched with the strings pityriasis rosea, atopic dermatitis/atopic eczema, and scabies and retrieved all medical records with these entities from March 1, 1999, to February 28, 2002. The diagnoses were all made clinically by trainers or trainees in family medicine. All had undergone hospital-based training that included training in dermatology in a format accredited by the Hong Kong College of Family Physicians.

We included a diagnosis of PR for analysis only if 3 of the following 4 clinical features were clearly and legibly documented on the medical record: (1) herald patch, (2) peripheral collarette scaling, (3) mainly truncal and proximal limb distribution, and (4) orientation of lesions along lines of skin cleavage, parallel to the ribs, or in a Christmas tree or anti–Christmas tree pattern. This is based on a set of diagnostic criteria validated by Chuh33 that has been applied in other studies.10,11

We documented the date of first diagnosis for each patient with PR and for patients with atopic dermatitis and scabies. We obtained data for the monthly mean air temperature, mean total rainfall, and mean relative humidity for the period studied from the Hong Kong Observatory. We analyzed the data with the nonparametric Spearman rank-order correlation coefficient (γs). All P values were calculated 2-tailed.

We analyzed the extent of temporal clustering by a method based on a regression model.30 The approach is first based on a transformation of the data set to produce values corresponding to the time (the distance) between successive cases. Under the nonclustering hypothesis, these values can be estimated by a constant. On the contrary, a piecewise constant model improves the fitting. We applied the method to obtain several models with different numbers of clusters. Once the cluster bounds had been computed for each model, we selected the model with the smallest Akaike information criteria34 value to determine the number of clusters. To avoid sample effects and to obtain a P value, we computed again the criteria on 1000 bootstrapped samples. The P value corresponds to the percentage of bootstrapped samples for which the cluster model is selected with the Akaike information criteria against the nonclustering model.

RESULTS

Six affiliated teaching practices agreed to participate. We searched the medical records and identified 41 cases of PR with the recorded clinical features fulfilling the criteria. Also identified were 564 cases of atopic dermatitis and 35 cases of scabies.

Of the 41 patients with PR, 20 were male and 21 were female (male-female ratio, 1:1.05). Their age ranged from 5 to 54 years (mean age, 25.9 years). The monthly incidence of PR was negatively correlated with monthly mean air temperature (γs = −0.41), ie, there were more cases of PR in the colder months. However, the correlation was insignificant (P = .19). Correlation with monthly mean total rainfall was also negative (γs = −0.34) but insignificant (P = .27). The monthly incidence was unrelated to monthly mean relative humidity (γs = −0.04, P = .91).

Three statistically significant clusters were identified for patients with PR. Figure 1 presents the distance between successive cases and the best piecewise constant regression function. A short mean time between successive events indicates a cluster. The statistical model with 3 clusters has a significant value (P = .03) compared with the nonclustering hypothesis. This model detected a cluster of 7 cases between February 4, 2000, and February 28, 2000, a cluster of 6 cases between July 3, 2000, and July 24, 2000, and a cluster of 7 cases between April 2, 2001, and April 28, 2001.

For the negative control condition of atopic dermatitis, the constant (nonclustering) regression model was selected by Akaike information criteria. For the positive control condition of scabies, 1 cluster of 20 cases was detected between January 30, 2002, and March 7, 2002 (P = .03) (Figure 2).

COMMENT

Using a regression model and applying the Akaike information criteria for selecting models, we identified 3 statistically significant temporal clusters in our series of patients with PR. Our results are compatible with the results of Messenger et al.23 We adopted a retrospective approach to eliminate reporting bias found in prospective studies.23,25 In addition, we supported the validity of our analysis by concomitant analysis of 2 control conditions, establishing the nonclustering model for atopic dermatitis (negative control condition) and identifying significant clustering for scabies (positive control condition). In contrast to the report by Messenger et al,23 which was criticized because the degree of clustering found was not valid to support an infectious hypothesis,24 our results should provide adequate evidence to establish temporal clustering in PR.

The age and sex distributions of our 41 patients with PR were similar to those in other epidemiologic studies on PR.18,23,25,3543 These studies are summarized in Table 1. Some studies23,37,39 reported higher incidence of PR in the colder months, one40 reported higher incidence in the early part of the rainy season, and some35,36,43 reported no seasonal variation.

We found slightly higher incidence of PR in the colder months and months with less rainfall, although such correlations were weak and insignificant. Seasonal variation could have contributed to apparent temporal clustering. However, the 3 clusters of cases of PR occurred in February 2000, July 2000, and April 2001. According to data from the Hong Kong Observatory, February is the second coldest month in the year, July is the second hottest month in the year, and April is a temperate month. The temporal clustering demonstrated is therefore highly likely to be genuine and independent of seasonal variation.

It has been postulated that PR may be due to reactivation of a latent virus rather than a primary viral infection.44 Is temporal clustering compatible with reactivation? We believe that it is. Varicella zoster is a typical viral reactivation disease. For unknown reasons, temporal clustering has also been demonstrated in that disease.45 We thus believe that further studies to investigate the question of primary infection or reactivation of pathogens are strongly warranted.

Our study has several limitations. Only a small number of patients with PR were identified during the study period. Underrecognition of this condition by primary care physicians might have been one important factor for this small number. We are unaware of any previously reported study on the epidemiology of PR in Hong Kong. We have tried to compare our number of patients with those of 2 epidemiology studies reported in Singapore.25,43 However, these 2 studies were performed in specialist settings, and a difference in the denominator renders direct comparison difficult. Another weakness is that the 6 participating practices were not randomly selected. Some selection bias could be present. Although a retrospective method does reduce reporting bias, some cases could have been missed.

Some patients may have visited a dermatologist instead of a primary care physician, and this may also contribute to the small number of patients. We elected to conduct this study in primary care settings rather than in specialist dermatology centers, as we believe that primary care morbidity is the closest proxy measure of a community diagnosis. Care in specialist settings cannot truly reflect the epidemiologic picture in the community. We opted to analyze the dates of first diagnosis rather than the estimated dates of rash onset, as many patients could have missed the herald patch (if any) or could not be definite about the rash onset date.

Epidemiologic data represent only one of several elements of factors supporting the association of PR and an infectious cause. We believe that such association is far from fulfilling Hill's causality criteria46—namely, strength, consistency, specificity, temporality, biological gradient, plausibility, coherence, experimental evidence, and analogy. However, as the epidemiologic evidence favors an infectious cause, further laboratory investigations to look for the underlying pathogen are strongly indicated.

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Article Information

Corresponding author and reprints: Antonio A. T. Chuh, MRCP(UK), MRCP(Irel), MRCPCH, DipDerm, Department of Medicine, University of Hong Kong, Queen Mary Hospital, Pokfulam Road, Hong Kong (e-mail: achuh@iohk.com).

Accepted for publication September 5, 2002.

We thank G. M. Leung, MD, Department of Community Medicine, University of Hong Kong, for his valuable comments on the manuscript. We also thank D. Tse, Hong Kong Observatory, for his permission to use the climate data in our analysis.

References
1.
Drago  FRanieri  EMalaguti  FLosi  ERebora  A Human herpesvirus 7 in pityriasis rosea. Lancet. 1997;3491367- 1368Article
2.
Drago  FRanieri  EMalaguti  FBattifoglio  MLLosi  ERebora  A Human herpesvirus 7 in patients with pityriasis rosea: electron microscopy investigations and polymerase chain reaction in mononuclear cells, plasma and skin. Dermatology. 1997;195374- 378Article
3.
Watanabe  TSugaya  MNakamura  KTamaki  K Human herpesvirus 7 and pityriasis rosea. J Invest Dermatol. 1999;113288- 289Article
4.
Kempf  WAdams  VKleinhans  M  et al.  Pityriasis rosea is not associated with human herpesvirus 7. Arch Dermatol. 1999;1351070- 1072Article
5.
Yoshida  M Detection of human herpesvirus 7 in patients with pityriasis rosea and healthy individuals [letter]. Dermatology. 1999;199197- 198Article
6.
Kosuge  HTanaka-Taya  KMiyoshi  H  et al.  Epidemiological study of human herpesvirus-6 and human herpesvirus-7 in pityriasis rosea. Br J Dermatol. 2000;143795- 798Article
7.
Offidani  APritelli  ESimonetti  OCellini  AGiornetta  LBossi  G Pityriasis rosea associated with herpesvirus 7 DNA. J Eur Acad Dermatol Venereol. 2000;14313- 314Article
8.
Wong  WRTsai  CYShih  SRChan  HL Association of pityriasis rosea with human herpesvirus-6 and human herpesvirus-7 in Taipei. J Formos Med Assoc. 2001;100478- 483
9.
Chuh  AAPeiris  JS Lack of evidence of active human herpesvirus 7 (HHV-7) infection in three cases of pityriasis rosea in children. Pediatr Dermatol. 2001;18381- 383Article
10.
Chuh  AAChiu  SSPeiris  JS Human herpesvirus 6 and 7 DNA in peripheral blood leucocytes and plasma in patients with pityriasis rosea by polymerase chain reaction: a prospective case control study. Acta Derm Venereol. 2001;81289- 290Article
11.
Chuh  AAChan  HH Prospective case-control study of chlamydia, legionella and mycoplasma infections in patients with pityriasis rosea. Eur J Dermatol. 2002;12170- 173
12.
Sharma  PKYadav  TPGautam  RKTaneja  NSatyanarayana  L Erythromycin in pityriasis rosea: a double-blind, placebo-controlled clinical trial. J Am Acad Dermatol. 2000;42 (2, pt 1) 241- 244Article
13.
Bosc  F Is pityriasis rosea infectious? Lancet. 1981;1662Article
14.
Not Available, Case clustering in pityriasis rosea: support for role of an infective agent. Br Med J (Clin Res Ed). 1982;2841478
15.
Halkier-Sorensen  L Recurrent pityriasis rosea: new episodes every year for five years: a case report. Acta Derm Venereol. 1990;70179- 180
16.
Bjornberg  AHellgren  L Pityriasis rosea: a statistical, clinical and laboratory investigation of 826 patients and matched healthy controls. Acta Derm Venereol. 1962;4250
17.
Chuang  TYPerry  HOIlstrup  DMKurland  LT Recent upper respiratory tract infection and pityriasis rosea: a case-control study of 249 matched pairs. Br J Dermatol. 1983;108587- 591Article
18.
Traore  AKorsaga-Some  NNiamba  PBarro  FSanou  IDrabo  YJ Pityriasis rosea in secondary schools in Ouagadougou, Burkina Faso [in French]. Ann Dermatol Venereol. 2001;128605- 609
19.
Vigh  G Observations on pityriasis rosea patients [in German]. Z Hautkr. 1983;581268- 1272
20.
McPherson  AMcPherson  KRyan  T Is pityriasis rosea an infectious disease? Lancet. 1980;21077Article
21.
Alexander  FEBoyle  PCarli  PM  et al.  Spatial temporal patterns in childhood leukaemia: further evidence for an infectious origin: EUROCLUS project. Br J Cancer. 1998;77812- 817Article
22.
Nakamura  YYanagawa  IKawasaki  T Temporal and geographical clustering of Kawasaki disease in Japan. Prog Clin Biol Res. 1987;25019- 32
23.
Messenger  AGKnox  EGSummerly  RMuston  HLIlderton  E Case clustering in pityriasis rosea: support for role of an infective agent. BMJ (Clin Res Ed). 1982;284371- 373Article
24.
Cameron  DJones  IG Case clustering in pityriasis rosea: support for role of an infective agent [letter]. Br Med J (Clin Res Ed). 1982;2841478Article
25.
Cheong  WKWong  KS An epidemiological study of pityriasis rosea in Middle Road Hospital. Singapore Med J. 1989;3060- 62
26.
Ederer  FMyers  MHMantel  N A statistical problem in space and time: do leukemia cases come in clusters? Biometrics. 1964;20626- 638Article
27.
Naus  JI The distribution of the size of the maximum cluster of points on a line. J Am Stat Assoc. 1965;60532- 538Article
28.
Kulldorff  MNagarwalla  N Spatial disease clusters: detection and inference. Stat Med. 1995;14799- 810Article
29.
Larsen  RJHolmes  CLHeath  CW  Jr A statistical test for measuring unimodal clustering: a description of the test and of its application to cases of acute leukemia in metropolitan Atlanta, Georgia. Biometrics. 1973;29301- 309Article
30.
Molinari  NBonaldi  CDaures  JP Multiple temporal cluster detection. Biometrics. 2001;57577- 583Article
31.
Knox  G Secular pattern of congenital oesophageal atresia. Br J Prev Soc Med. 1959;13222- 226
32.
Berthier  FBoulay  FMolinari  NDaures  JPBlaive  B Rôle de la température sur l'existence de macro agrégats hivernaux d'hémoptysies. Rev Mal Respir. 2000;17 (suppl) 1S125
33.
Chuh  AAT Diagnostic criteria for pityriasis rosea—a prospective case control study for assessment of validity. J Eur Acad Dermatol Venereol. 2003;17101- 103Article
34.
Akaike  H Information theory and an extension of the maximum likelihood principle. Petrov  BNCsaki  Feds.2nd International Symposium on Information Theory Budapest, Hungary Akademiai Kiado Budapest1973;267- 281
35.
Vollum  DI Pityriasis rosea in the African. Trans St Johns Hosp Dermatol Soc. 1973;59269- 271
36.
Jacyk  WK Pityriasis rosea in Nigerians. Int J Dermatol. 1980;19397- 399Article
37.
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