Perceived risk, anxiety, and behavioural responses of the general public during the early phase of the Influenza A (H1N1) pandemic in the Netherlands: results of three consecutive online surveys

Marloes Bults
Desirée Jma Beaujean
Onno De Zwart
Gerjo Kok
Pepijn Van Empelen
Jim E Van Steenbergen
Jan Hendrik Richardus
Hélène Acm Voeten
Perceived risk, anxiety, and behavioural responses of the general public during the early phase of the Influenza A (H1N1) pandemic in the Netherlands: results of three consecutive online surveys
R E S E A R C H A R T I C L E Open Access
Background: Research into risk perception and behavioural responses in case of emerging infectious diseases is still relatively new. The aim of this study was to examine perceptions and behaviours of the general public during the early phase of the Influenza A (H1N1) pandemic in the Netherlands. Methods: Two cross-sectional and one follow-up online survey (survey 1,

Background

At the end of April 2009, an outbreak of a new Influenza A (H1N1) virus occurred in Mexico and the United States, spreading rapidly to other countries worldwide. The Influenza A (H1N1) virus has became the dominant influenza strain in most parts of the world. Up to January 2010, around 14000 deaths related to Influenza A (H1N1) were reported worldwide [1]. The virus can cause very severe and fatal illness, but the majority of patients experience mild symptoms comparable to the common seasonal influenza. Important differences with the seasonal flu exist. For example, most severe cases and deaths have occurred in adults under 50 years of age, and severe respiratory failure has been reported more frequently in young and healthy persons [2]. When the World Health Organisation (WHO) raised the pandemic alert to phase 6, the focus shifted towards delaying viral spread through population-based measures, such as hand and respiratory hygiene, and voluntary isolation of symptomatic persons [3][4][5].

In the Netherlands, a new vaccine against the Influenza A (H1N1) virus became available for specific risk groups in November 2009 [6]. Nevertheless, during the 2009 Influenza A (H1N1) pandemic, behavioural responses of the general public were very important in limiting spread of the virus. Compliance with preventive measures, such as non-medical interventions, antiviral treatment, and vaccination, is dependent upon the willingness and ability of the general public. Compliance with preventive measures is not self-evident. During the SARS epidemic in 2003, the use of face masks was low among adults in Hong Kong and air travellers with influenza-like symptoms [7,8]. In the Netherlands, during an outbreak of avian Influenza among poultry in 2003, large groups of the population did not adhere to personal protective measures or instructions regarding prophylaxis [9].

Surveillance of perceptions and behavioural responses of the general public during pandemics provides useful information for health risk communication and achieving successful changes in public behaviour [10,11]. In recent years, a number of studies have been published on risk perception and public responses in case of a pandemic influenza [12][13][14][15][16][17][18][19]. These studies were conducted prior to the occurrence of the 2009 Influenza A (H1N1) pandemic, in times when pandemic influenza was not regarded as a high threat and information was based on hypothetical scenarios. During the 2009 influenza pandemic a number of studies have been conducted among the general public on risk perception of the Influenza A (H1N1) and intention to take preventive measures [20][21][22]. These studies consisted of a single, cross-sectional survey. In the present study we aimed to examine perceived risk, feelings of anxiety, and behavioural responses of the Dutch general public related to the outbreak of Influenza A (H1N1) over a period with changing risks and publicity. The first objective of this study was to identify trends over time in risk perception, feelings of anxiety, and behavioural responses (survey 1-3). The second objective was to assess factors significantly associated with taking preventive measures and strong intention to comply with government-advised preventive measures in the future (survey 3).

Methods

Timing of the three surveys related to the course of the Influenza A (H1N1) outbreak

The first survey started on 30 April 2009, when the first case of Influenza A (H1N1) was confirmed in the Netherlands. At that time there were 27 confirmed Influenza A (H1N1) cases in eight different European Union (EU) countries. The first survey ended on 4 May, when the number of cases in the EU had increased to more than 100, including 15 human-to-human transmissions [23,24]. The second survey started on 15 June 2009, when there was sustained transmission of the Influenza A (H1N1) virus in several countries and the WHO raised the pandemic alert status to phase 6, characterized by human-to-human spread and community-level outbreaks in more than one WHO region. At that time, there were confirmed cases in 82 countries, including 167 deaths. In the Netherlands, the number of confirmed cases had increased to 60. The second data collection period ended on 19 June; when there were more than 200 deaths worldwide [25,26]. The follow-up survey took place from 11 to 20 August 2009, when the Netherlands counted 1021 confirmed cases, including the first fatal case [27]. On 20 August, the total number of reported and confirmed pandemic influenza cases in the world was 24,8941, including 2430 deaths [27,28].

Participants

At three different time points, an online survey was filled out by a representative Internet panel, named the Flycatcher panel http://www.flycatcher.eu. This panel consists of people from the Dutch general public who volunteer to participate in online questionnaire surveys. The Flycatcher panel consists of 20,000 members. The distribution of demographic variables (gender, age, region, and level of education) of the panel members is comparable to the general Dutch population. The panel meets high quality requirements and is ISO-certified. For the first and second survey, independent random samples were drawn of approximately 1000 panel members aged 18 years and older. All respondents of the first and second survey were invited to participate in the third (follow-up) survey. Panel members who participated in the first or second survey but did not respond to the follow-up survey (n = 255) were excluded from further analyses. Sampled panel members were invited to participate in this study by sending an email with an Internet link. The surveys were online for a period ranging from 5 to 10 days. Panel members received 1.50 Euro in credits for completion of the survey, which could be exchanged for gift vouchers.

The nature of this general Internet-based survey amongst healthy volunteers from the general population does not require formal medical ethical approval according to the Dutch law [29].

Online questionnaire

An online questionnaire was developed based on an existing questionnaire used in studies on risk perception and precautionary behaviours of the general public during outbreaks of SARS [30] and avian Influenza [31]. The questionnaire was based on an integrated model to explain health behaviour, including constructs from the Protection Motivation Theory (PMT) [32] and the Health Belief Model (HBM) [33]. These theories were applied because risk perception is one of the central constructs. Risk perception is specified as a combination of perceived severity (a person's belief on how serious contracting the illness would be for him/her) and perceived vulnerability (a person's perception of the chance that he/she will contract the disease). Furthermore, the PMT has two other key constructs besides risk perception, namely response efficacy (a person's belief in the effectiveness of the preventive measure) and self efficacy (a person's level of confidence in his/her ability to perform the preventive measure). The PMT states that a high risk perception will only lead to preventive behaviour if response efficacy and self-efficacy are also high. To examine perceived risk and factors associated with taking preventive measures during the 2009 influenza pandemic we included the following constructs: perceived severity of and vulnerability to Influenza A (H1N1), perceived efficacy of preventive measures, and a persons' ability (self-efficacy) and intention to take measures. Participants were asked about preventive measures against the new flu, namely: 'avoiding crowded places'; 'practicing better hygiene (washing hands more frequent, using tissues when coughing or sneezing)'; 'avoiding persons with Influenza A (H1N1)'; 'wearing face mask'; 'seeking medical advice with the onset of flu symptoms'; 'taking antiviral medication (i.e. Tamiflu)'; and 'staying home from school or work'. In the second and third surveys an additional measure was included: 'getting vaccinated with a new vaccine'. Questions about feelings of anxiety for Influenza A (H1N1) were also added [34]. Maladaptive responses are behaviours which does not protect one's health. Maladaptive responses may result in a lack of following advice from public health authorities. In the second and third surveys maladaptive response items were included and phrased as statements on underestimation, fatalism, and avoidance. The questionnaire concluded with items on amount of information received on Influenza A (H1N1), attention paid to the information, reliability and sufficiency of information provided by the government, information needs, and preferences for ways of communication during the further course of the Influenza pandemic. Knowledge was examined by statements concerning modes of transmission, infectiousness, feasibility of symptoms, and fatality of Influenza A (H1N1). The questionnaire was similar across the three survey rounds (Additional file 1). For knowledge, a summary score was created based on the number of correct answers and dichotomized as 0 (<4 items correct) or 1 (≥4 items correct). For all other constructs with 2 or more items, Cronbach's alpha was calculated. The Cronbach's alpha of the constructs ranged from 0.6 to 0.9. Therefore, a summary score was formulated by adding up the scores of the individual items, and dichotomized on the median.

Analysis

Time trends were analyzed using the Chi-square test for differences between surveys 1 (May 2009) and 2 (June 2009). Survey 3 of August 2009 was divided into 3.1 (follow-up of survey 1), and 3.2 (follow-up of survey 2); the Mc-Nemar test was used for analyzing differences between surveys 1 and 3.1 and between 2 and 3.2. Univariate and multivariate logistic regression analyses were performed to identify factors significantly associated with taking one or more preventive measures and strong intention to comply with government-advised preventive measures in the future. For the regression analyses we used data from survey 3 (August 2009), when a substantial amount of people took preventive measures (resp. 40%) compared to survey 1 and 2 (resp. 11% and 14%). For the multivariate regression analyses, all factors with a p-value <0.1 in the univariate analysis were entered in the multivariate model, and removed one-by-one (starting with the most insignificant one etc.) until only statistically significant predictors (p < 0.05) remained.

Results

Response rates and demographic characteristics

During the first survey in May 2009, 973 panel members were invited and 59% completed the online questionnaire. During the second survey in June 2009, 981 panel members were invited with a response rate of 63%. Of the 1192 respondents from the first two rounds who were invited for the follow-up survey in August, 79% completed the questionnaire.

Demographic characteristics of respondents are listed in Table 1. Overall, there were no significant differences between surveys. Focusing on survey 3, mean age was 51 years (range 19-89 years) and most respondents (92%) were of Dutch origin. Thirty-eight percent had a lower education (i.e. primary education, lower general or lower vocational education or less), 36% an intermediate (i.e. secondary general or vocational education), and 26% a higher education (i.e. higher professional education or university). The majority of respondents were employed. About three quarters were married or cohabitating and in 27% of the households there were one or more children under 18 years. Compared to the general Dutch population (Table 1), the respondents were older, more often of Dutch origin, and more often unemployed/ retired.

Time-trends in perceived risk, feelings of anxiety, and behavioural responses

The level of knowledge regarding Influenza A (H1N1) was generally high ( Table 2). The percentage of respondents who answered 4 or more out of 6 items correctly increased significantly over time during the survey period, from 88% in May to 95% in August 2009 (for the survey in August, we refer to the results of survey 3.2). Only knowledge regarding the availability of a vaccine (which was not available before November 2009) decreased.

The percentage of respondents who reported a high perceived severity of Influenza A (H1N1) decreased from 80% in May to 39% in August 2009, whereas a high perceived vulnerability increased from 5% in June to 15% in August ( Table 2). Feelings of anxiety decreased from 16% in May to 4% in August reporting being (very) scared for the new flu. The perceived efficacy of preventive measures was highest for practicing better hygiene, avoiding regions with the new flu or persons with influenza-like symptoms, and seeking medical advice with the onset of flu symptoms; the percentage who perceived these measures to be effective ranging from 66% to 89% in August 2009. At the same time respondents felt confident to practice these preventive measures (perceived self-efficacy) ranging from 66% who felt confident to avoid persons with the new flu to 88%   who felt confident to practice better hygiene. The intention to comply decreased significantly over the three surveys for four out of seven preventive measures. The highest intention to comply was reported for practicing better hygiene and seeking medical advice, the lowest for staying home from school or work and wearing a face mask. The percentage of respondents who were likely to get vaccinated against Influenza A (H1N1) (when advised by the government) decreased from 77% in June to 63% in August. Over time, more respondents agreed with the statement that the threat of the new flu was exaggerated by the media or government (35% June, 58% August) and that it would not be as bad as predicted (28% June, 49% August). Also, a larger number of respondents were in agreement with the statement 'we just have to accept it', increasing from 24% in May to 47% in August.

The amount of received information about Influenza A (H1N1) decreased significantly between May and June and increased between June and August 2009, with the percentage of respondents who received (very) much information increasing from 37% to 48%. Information from the government was found less reliable over time; 62% found the information of the government reliable in May; in August 2009 this value decreased to 45%. In August, 70% reported a need for more information, mainly regarding details on the symptoms of Influenza A (H1N1) (30%), how to prevent infection (27%), and how it can be treated (16%) (data not shown). The preferred method for receiving this information was television (47%), Internet (36%), and newspapers (36%). The respondents preferred this information to be given by local or national health institutes or their general practitioner.

There was an increase in the percentage of respondents who had taken any preventive measure between June (14%) and August 2009 (38%). Practicing better hygiene was reported most often, by 36% of the respondents at the last survey. For the specific measures, a significant increase over time was observed for practicing better hygiene (12% in June, 36% in August), avoiding persons with influenza like symptoms (4% in June, 9% in August), and avoiding crowded places (3% in June, 8% in August) ( Table 2).

Factors associated with taking preventive measures and strong intention to comply (survey 3)

Univariate and multivariate logistic regression analyses were performed to identify factors significantly associated with: 1) taking one or more preventive measures and 2) strong intention to comply with governmentadvised preventive measures in the future (Table 3). In this regression analysis variables of the survey in August (survey 3) were included.

Factors univariately associated with taking preventive measures but not significant in the multivariate analysis were: perceived severity, vulnerability, and efficacy of measures; underestimation and fatalism statements; amount of information received, and reliability of governmental information. From multivariate logistic regression analysis, predictors of taking preventive measures were no children in the household (OR 1.45; 95% CI 1.04-2.0), high anxiety (OR 1.93; 95% CI 1.43-2.61), higher level of self-efficacy (OR 1.68; 95% CI 1.26-2.22), We also took a strong intention to comply with measures in the near future, when advised by the government, as an outcome (dependent) variable in the logistic regression analyses. Factors that were univariately associated but not significant in the multivariate analysis were: gender, level of education, employment status, marital status, perceived vulnerability, underestimation, fatalism, and avoidance statements, and attention paid to the information on Influenza A (H1N1

Discussion

In this population-based study performed in the Netherlands, we found that the level of knowledge regarding Influenza A (H1N1) increased between May and August 2009. At the same time, perceived severity of the new flu, perceived self-efficacy, and intention to comply with preventive measures decreased. The perceived reliability of information from the government also decreased from May to August. Feelings of anxiety decreased from May to June, and remained stable afterwards. From June to August 2009, perceived vulnerability increased and more respondents took preventive measures. Factors associated with taking preventive measures included no children in the household, high anxiety, high self-efficacy, agreeing with avoidance statements, and paying much attention to media information regarding Influenza A (H1N1). Having a strong intention to comply with government-advised preventive measures in the future was associated with older age, high perceived severity, high anxiety, high perceived efficacy of measures, high self-efficacy, and finding governmental information to be reliable.

A clear strength of this study is that data collection took place during the 2009 Influenza A (H1N1) pandemic, in contrast to other studies performed at times when pandemic influenza was not regarded as a high threat and scenarios were based on hypothetical situations [12][13][14][15][16][17][18][19]. Another strength is that this study consists of three repeated survey rounds, enabling analysis of trends over time. This is in contrast to other recent studies, which consisted of a single cross-sectional survey [20][21][22]. Moreover, we followed-up individuals, guaranteeing that differences between survey rounds were not due to differences between study populations, but represent real trends over time [35]. Finally, we used an online questionnaire, which creates less social desirability bias than personal telephone interviews. The use of an Internet panel led to high response rates: 59%, 63%, and 79% in survey 1, survey 2, and survey 3, respectively. Our study also has several limitations. First, the Internet panel members who responded to our online questionnaire were not fully representative of the general Dutch population. In our study, participants were more likely to be in the older age group (> 50 years) (52% versus 44%), of Dutch ethnicity (92% versus 80%), and unemployed/retired (43% versus 24%). We cross tabulated all the measured constructs by age group (18-49 years/> 50 years), employment status (employed/unemployed) and ethnicity (Dutch/non-Dutch) (data not shown). For these constructs, there were no differences between the Dutch and non-Dutch participants. Among both the older and unemployed the perceived efficacy, self efficacy and intention to comply with measures were significantly higher, and they more agreed with statements on avoidance. Perceived vulnerability and reliability of governmental information were lower among both the older and unemployed. Furthermore, the older age group paid more attention to the information of the government. Among the unemployed the perceived severity was higher and they less agreed with the underestimation statements. This population difference may have led to a substantial bias in the absolute outcomes of Table 2, but only to a small bias in the trends over time or in the predictors of behavioural responses. Second, in the logistic regression analyses we may have lost some power, because we used dichotomized summary scales as predictors. However, we have performed additional regression analyses with the predictors as continuous variables, and found minimal differences (data not shown). Third, the validity of the questionnaire used in this study was not tested through a test-retest design, because the Influenza pandemic was ongoing and thus perceptions were not stable over time. Fourth, no data were obtained from non-responders. This is the first national study to evaluate perceived risk, feelings of anxiety, and behavioural responses regarding Influenza A (H1N1) among the general public in the Netherlands. There was a decrease over time in perceived severity, anxiety and intention to comply with preventive measures. Initially, representatives of (inter) national health institutes predicted a worse-case scenario with large numbers of fatal cases, based on influenza pandemics in the past and early reports concerning the new Influenza virus [36]. In the following months, media attention decreased considerably, local viral transmission remained relatively limited in the Netherlands,  and the Dutch government announced that the pandemic appeared to be mild [37,38]. Decreasing trends over time in perceived severity and anxiety are consistent with the reality: the clinical picture of influenza turned out to be mild in course of time. The decrease in perceived reliability of information from the government was not surprisingly; in the beginning the general public believed the pandemic would be severe as pronounced by the government, but this turned out to be mild. This decrease in perceived reliability of governmental information was not alarming and did not result in more feelings of anxiety or in a lower intention to comply with measures. For this reason, respondents were not only asked about preventive measures they had taken, but also about their intention to comply with government-advised preventive measures in the near future. People who took preventive measures during this 'pre-phase' of governmental advice were very alert to media information and seemed to be practicing preventive measures based on emotions such as anxiety. This is in line with results of the study conducted by Jones et al. [20] concluding that affective variables, such as self-reported anxiety over the epidemic, mediate the likelihood that respondents engage in protective behaviour. Rubin et al. [21] also found a significant association between anxiety and carrying out recommended behaviours. Similarly, studies on outbreaks of SARS found that anxiety was associated with taking preventive measures [39,40]. To date, there are only few published studies assessing factors that might explain compliance with preventive behaviours in case of an Influenza pandemic. Comparison with these studies is difficult because of differences in phrasing of questionnaire items and methods of analysis. Barr et al. [14] collected baseline data about willingness to comply with vaccination, isolation, and wearing a face mask among Australians during a hypothetical influenza pandemic, and found a higher level of willingness to comply among people with higher levels of threat perception and among those of older age. This is in agreement with our findings, where intention to comply with measures was also associated with older age and high perceived severity. This is one of the first studies conducted during the course of the Influenza pandemic. Additional studies on risk perception among the public are needed to further understand the field of preventive behaviour as related to control of infectious diseases. Furthermore, these studies need to address emotional aspects such as anxiety, uncertainty, or embarrassment that play a role in decision making. Finally, research regarding the translation of results from the above-suggested studies into risk communication is of utmost importance.

Our study has several implications for health authorities and public health policy. In case of an emerging infectious disease, as Influenza A (H1N1), it is very difficult to predict the further course of the outbreak. It is important that health authorities present a range of scenarios, not only worst-case but also other, more positive, scenarios. In the beginning of an outbreak, there are many uncertainties about the infectiousness and case fatality rate of the disease. Health authorities should not only communicate with the public about 'what is known' (the certainties), but they should also communicate about 'what is not known' (the uncertainties). In course of the outbreak, when more information becomes available, public health authorities should update their messages to achieve effective risk communication. This is essential not only to instruct and motivate the public to take preventive measures, but also to build trust in public health authorities and prevent misconceptions. Besides rational arguments (such as perceived severity and efficacy of measures), emotional aspects like anxiety play a role in decision making concerning preventive behaviour. Health authorities should acknowledge these emotional aspects and take these arguments into account in their risk communication with the general public.

Conclusion

Decreasing trends over time in perceived severity and anxiety are consistent with the reality: the clinical picture of influenza turned out to be mild in course of time. Although (inter)national health authorities initially overestimated the case fatality rate, the public stayed calm and remained to have a relatively high intention to comply with preventive measures. During future outbreaks of infectious diseases it is important that health authorities present a range of scenarios, not only worstcase but also other, more positive, scenarios. Health authorities should not only communicate with the public about 'what is known' (the certainties), but they should also communicate about 'what is not known' (the uncertainties). In course of the outbreak, when more information becomes available, public health authorities should update their messages to instruct and motivate the public to take preventive measures, to build trust in public health authorities and prevent misconceptions.

Additional material

Additional file 1: Survey questions 'Risk perception and behavioural responses of the general public during the Influenza A (H1N1) pandemic in the Netherlands'. This questionnaire was used across the three survey rounds.

Table 1
1Demographic characteristics of respondents, survey 1, 2 and 3Characteristics
Survey 1
Survey 2
Survey 3
follow-up

Data Statistics NL

30 April-4 May
15-19 June
11-20 August
1-1-2009

(n = 456)
(n = 478)
(n = 934)

Sex

Male
52%
52%
52%
50%

Female
48%
49%
48%
51%

Age

18-29 years
13%
12%
12%
18%

30-49 years
33%
40%
36%
37%

Above 50 years
55%
49%
52%
44%

Ethnicity
Dutch
90%
92%
92%
80%

Non-dutch
10%
8%
8%
20%

Education

Low
40%
39%
38%
33%

Intermediate
38%
38%
36%
41%

High
22%
23%
26%
25%

Employment status

Employed
-
61%
57%
76%
Unemployed/Retired
-
40%
43%
24%

Marital status

Single
-
17%
19%

Married/Cohabitating
-
76%
73%

Divorced/Widowed
-
7%
7%

Children < 18 years in household

Yes
-
27%
27%

No
-
73%
73%

'-' data not collected in survey 1.

Bults et al. BMC Public Health 2011, 11:2
http://www.biomedcentral.com/1471-2458/11/2

Table 2
2Trends over time in risk perception, anxiety and behavioural responses Knowledge 1. The new flu is caused by a new influenza virus (correct)Survey 1
30 April-
4 May
(n =
456)

Survey
2
15-19
June
(n =
478)

P-value  †
survey
1 vs. 2

Survey
3.1
follow-up τ
11-20
August
(n = 456)

P-value  ‡
survey
1 vs. 3.1

Survey 3.2
follow-up π
11-20
August
(n = 478)

P-value  ‡
survey
2 vs. 3.2

Time trend

1-2 2-3

74%
79%
ns
84%
< 0.001
86%
< 0.001
ns +

2. A vaccine is available against the new flu
(incorrect)  §

50%
47%
ns
37%
< 0.001
36%
< 0.001
ns -

3. The new flu can be transmitted by human-
to-human contact (correct)

97%
98%
ns
98%
ns
99%
ns
ns ns

4. People died from the new flu (correct)
97%
97%
ns
99%
0.03
99%
ns
ns ns

5. The new flu can be transmitted through
eating pork (incorrect)

91%
90%
ns
95%
0.004
94%
0.01
ns +

6. Symptoms of the new flu are visible
(incorrect)

81%
81%
ns
90%
< 0.001
87%
< 0.001
ns +

7. A flu pandemic occurs once in 10-50 years
(correct)

-
56%
-
50%
-
60%
ns
ns

Summary score (4 or more correctly answered)
88%
92%
0.02
96%
< 0.001
95%
0.05
+ +

Perceived severity (scale 1-5)

1. Severity of the new flu (score 4-5, severe-
very severe)

80%
67%
< 0.001
43%
< 0.001
39%
< 0.001
--

2. Severity of getting the new flu coming year
(score 4-5, severe-very severe)

70%
61%
0.002
39%
< 0.001
39%
< 0.001
--

3. The new flu is very harmful for my health
(score 4-5, mostly-totally agree)

-
49%
-
31%
-
27%
< 0.001
-

Summary score items 1-2 (high) -Chronbach alpha
0.8

64%
53%
< 0.001
29%
< 0.001
29%
< 0.001
--

Perceived vulnerability (scale 1-5)

1. Perceived susceptibility (score 4-5, quite-very
susceptible)

18%
22%
ns
26%
0.02
30%
0.003
ns +

2. Perceived chance of getting infected next
year (score 4-5, likely-very likely)

5%
5%
ns
15%
< 0.001
15%
< 0.001
ns +

3. Perceived chance of getting infected
compared to others
(score 4-5, more-much more)

6%
6%
ns
9%
ns
12%
< 0.001
ns +

Summary score (high) -Chronbach alpha 0.6
15%
16%
ns
29%
< 0.001
31%
< 0.001
ns +

Perceived anxiety (scale 1-5)

1. Worried about the new flu (score 4-5,
worried-very worried)

36%
19%
< 0.001
16%
< 0.001
14%
0.02
--

2. Fear for the new flu (score 4-5, scared-very
scared)

16%
8%
< 0.001
6%
< 0.001
4%
0.009
--

3. Thinking about the new flu (score 4-5,
often-very often)

27%
9%
< 0.001
12%
< 0.001
15%
0.003
-+

Summary score (high) -Chronbach alpha 0.8
61%
40%
< 0.001
39%
< 0.001
36%
ns
-ns

Perceived efficacy (scale 1-5; certainly not-
certainly)

1. Keep away from crowded places (score 4-5)
55%
47%
0.01
58%
ns
54%
0.01
-+

2. Practice better hygiene (score 4-5)
80%
75%
ns
89%
< 0.001
89%
< 0.001
ns +
3. Avoid regions/persons ¥ with new flu (score
4-5)

82%
73%
0.001
74%
0.002
73%
ns
-ns

4. Wear face mask (score 4-5)
34%
31%
ns
22%
< 0.001
25%
0.009
ns -

5. Seek medical advice with the onset of flu
symptoms (score 4-5)

78%
72%
0.03
70%
< 0.001
66%
0.03
--

6. Take antiviral medication (score 4-5)
37%
46%
0.005
40%
ns
39%
0.01
+ -

Table 2
2Trends over time in risk perception, anxiety and behavioural responses (Continued)7. Stay home from school or work (score 4-5)
18%
21%
ns
33%
< 0.001
31%
< 0.001
ns +

8. Get a new vaccine against the new flu
(score 4-5)

-
54%
-
49%
-
53%
ns
ns

Summary score items 1-7 (high) -Chronbach alpha
0.7

50%
38%
< 0.001
50%
ns
50%
< 0.001
-+

Perceived self-efficacy* (scale 1-5; certainly not-
certainly)

1. Keep away from crowded places (score 4-5)
67%
61%
ns
56%
< 0.001
50%
< 0.001
ns -

2. Practice better hygiene (score 4-5)
91%
88%
ns
89%
ns
88%
ns
ns ns

3. Avoid regions/persons ¥ with new flu (score
4-5)

89%
78%
< 0.001
64%
< 0.001
66%
< 0.001
--

4. Wear face mask (score 4-5)
71%
60%
< 0.001
50%
< 0.001
47%
< 0.001
--

5. Seek medical advice with the onset of flu
symptoms (score 4-5)

91%
87%
0.05
87%
0.02
86%
ns
-ns

6. Take antiviral medication (score 4-5)
80%
80%
ns
71%
0.001
70%
< 0.001
ns -
7. Stay home from school or work (score 4-5)
56%
50%
ns
52%
ns
50%
ns
ns ns

8. Get a new vaccine against the new flu
(score 4-5)

-
79%
-
69%
-
70%
< 0.001
-

Summary score items 1-7 (high) -Chronbach alpha
0.9

55%
43%
< 0.001
38%
< 0.001
35%
0.001
--

Intention* (scale 1-5; certainly not-certainly)

1. Keep away from crowded places (score 4-5)
76%
66%
0.001
62%
< 0.001
59%
0.001
--

2. Practice better hygiene (score 4-5)
93%
89%
ns
91%
ns
89%
ns
ns ns

3. Avoid regions/persons ¥ with new flu (score
4-5)

89%
81%
0.001
71%
< 0.001
72%
< 0.001
--

4. Wear face mask (score 4-5)
70%
57%
< 0.001
46%
< 0.001
44%
< 0.001
--

5. Seek medical advice with the onset of flu
symptoms (score 4-5)

91%
89%
ns
84%
< 0.001
84%
0.01
ns -

6. Take antiviral medication (score 4-5)
82%
76%
0.02
66%
< 0.001
65%
< 0.001
--

7. Stay home from school or work (score 4-5)
61%
53%
0.01
56%
ns
50%
ns
-ns

8. Get a new vaccine against the new flu  §
(score 4-5)

-
77%
-
67%
-
63%
0.001
-

Summary score items 1-7 (high) -Chronbach alpha
0.9

60%
48%
< 0.001
41%
< 0.001
41%
0.006
--

Maladaptive response (scale 1-5; totally
disagree-totally agree)

The threat is exaggerated by media and
government (score 4-5)

-
35%
-
56%
-
58%
< 0.001
+

It will not be as bad as predicted (score 4-5)
-
28%
-
49%
-
49%
< 0.001
+

Summary score -underestimation statements
(high) -Chronbach alpha 0.6

-
20%
-
40%
-
42%
< 0.001
+

There is nothing we can do about it (score 4-
5)

-
5%
-
14%
-
16%
< 0.001
+

We will all be completely powerless (score 4-5)
-
7%
-
14%
-
14%
< 0.001
+

We will just have to accept it (score 4-5)
-
24%
-
43%
-
47%
< 0.001
+
Summary score -fatalism statements (score 4-5) -
Chronbach alpha 0.6

-
26%
-
48%
-
44%
< 0.001
+

I will move to a place without influenza (score
4-5)

-
2%
-
1%
-
0%
0.04
-

I will stock up and stay indoors (score 4-5)
-
3%
-
2%
-
4%
ns
ns
Summary score -avoidance statements (high) -
Chronbach alpha 0.7

-
52%
-
39%
-
38%
< 0.001
-

Information (scale 1-5)

Amount of information received (score 4-5,
much-very much)

52%
37%
< 0.001
53%
ns
48%
< 0.001
-+

Attention paid to information received (score
4-5, much-very much)

30%
21%
0.002
21%
< 0.001
23%
ns
-ns

Table 2
2Trends over time in risk perception, anxiety and behavioural responses (Continued)Is information of the government reliable?
(score 4-5, reliable-very reliable)

62%
53%
0.004
48%
< 0.001
45%
0.002
--

Is information of the government sufficient?
(score 4-5, sufficient-very sufficient)

58%
42%
< 0.001
52%
0.02
47%
ns
-ns

Measures taken

Practiced better hygiene
8%
12%
ns
36%
< 0.001
36%
< 0.001
ns +

Avoided persons with influenza-like symptoms
-
4%
-
10%
-
9%
< 0.001
+

Avoided crowded places
3%
3%
ns
7%
0.003
8%
< 0.001
ns +
Cancelled or did not book a holiday to areas
with the new flu

0.2%
0.4%
ns
0.9%
ns
1%
ns
ns ns

Bought face mask
0.4%
1%
ns
0.7%
ns
2%
ns
ns ns
Bought antiviral medication
0.2%
0.4%
ns
0.4%
ns
2%
ns
ns ns

Something else
1%
2%
ns
2%
ns
1%
ns
ns ns

Summary score (any measures taken)
11%
14%
ns
40%
< 0.001
38%
< 0.001
ns +

vs = versus;  † p-value obtained using Chi 2 tests;  ‡ p-value obtained using McNemar tests; τ follow-up of survey 1; π follow-up of survey 2; '-' data not collected in
survey 1;
'+' indicates a significant increase over time; '-' indicates a significant decrease over time; ns = not statistically significant.
¥ In the third survey 'avoiding regions with Influenza A (H1N1)' was changed into 'avoiding persons with influenza like symptoms'.

* Respondents were asked to imagine that governmental health institutes would recommend the preventive behaviour.
 § A vaccine against Influenza A (H1N1) became available in the Netherlands in November 2009.

Table 3
3Predictors of taking preventive measures and strong intention to comply with measures regarding Influenza A (H1N1)Taking one or more preventive measures
Strong intention to comply with government-advised
preventive
measures in the future  †

Row
%

OR u 95% CI p-value OR m 95% CI p-value Row
%

OR u 95% CI p-value OR m 95% CI p-value

Demographic
characteristics

Sex

male
36.9 1.00
45.3 1.00

female
41.5 1.21 0.93-1.58
0.1
-
-
-
53.0 1.36 1.05-1.76
0.02
-
-
-

Age

18-29 years
35.1 1.00
ns
-
-
-
28.9 1.00
<0.001 1.00
0.007

30-49 years
36.2 1.05 0.67-1.64
44.2 1.95 1.23-3.08
1.77 0.94-3.35
above 50 years
42.0 1.34 0.88-2.05
57.1 3.27 2.10-5.10
2.61 1.39-4.90

Ethnicity

Dutch
39.1 1.00
ns
-
-
-
49.4 1.00
ns
-
-
-

non-Dutch
39.0 1.00 0.62-1.60
45.5 0.86 0.54-1.37

Education

low
37.8 1.00
ns
-
-
-
56.3 1.00
0.002
-
-
-

intermediate
40.2 1.11 0.82-1.50
45.9 0.66 0.49-0.89

high
39.3 1.07 0.76-1.49
42.6 0.58 0.42-0.80
Employment status

employed
38.9 1.00
ns
-
-
-
41.5 1.00

unemployed/
retired

39.4 1.02 0.78-1.33
58.9 2.02 1.55-2.63 <0.001
-
-
-

Marital status

single
39.4 1.00
ns
-
-
-
41.7 1.00
0.04

married/cohabited 39.3 0.99 0.71-1.39
50.1 1.40 1.01-1.96

divorced/widowed 36.2 0.87 0.49-1.55
58.0 1.93 1.10-3.39
-
-
-

Children < 18 yrs
in household

yes
34.0 1.00
1.00
44.8 1.00

no
40.9 1.35 0.99-1.82
0.06
1.45 1.04-2.00
0.03
50.6 1.27 0.94-1.69
0.1
-
-
-
Knowledge score

<4
36.5 1.00
47.0 1.00
ns
-
-
-
≥4
41.1 1.22 0.93-1.59
0.1
-
-
-
50.6 1.15 0.89-1.49

Perceived severity
(summary score)

low severity
34.0 1.00
37.3 1.00
1.00

high severity
44.5 1.56 1.20-2.03 0.001
-
-
-
61.7 2.71 2.08-3.53 <0.001 1.62 1.07-2.44
0.02

Perceived
vulnerability
(summary score)

low vulnerability
35.4 1.00
45.2 1.00

high vulnerability
47.5 1.66 1.25-2.20 <0.001
-
-
-
57.7 1.66 1.25-2.19 <0.001
-
-
-

Anxiety (summary
score)

low anxiety
30.6 1.00
1.00
39.5 1.00
1.00

high anxiety
53.1 2.57 1.96-3.38 <0.001 1.93 1.43-2.61 <0.001 64.8 2.81 2.14-3.70 <0.001 2.22 1.44-3.42 <0.001

Perceived efficacy
(summary score)

low efficacy
32.8 1.00
31.0 1.00
1.00
high efficacy
46.4 1.77 1.36-2.31 <0.001
-
-
-
70.1 5.21 3.94-6.89 <0.001 2.57 1.77-3.74 <0.001

Table 3
3Data from survey 3 were used for the regression analyses (August 2009, n = 934). OR u : univariate odds ratio; OR m : multivariate odds ratio; ns: not statistically significant. Included preventive measures, i.e. 1) keep away from crowded places; 2) practice better hygiene; 3) avoid persons with the new flu; 4) wear face mask; 5) seek medical advice with the onset of flu symptoms; 6) take antiviral medication; 7) stay home from school or work; 8) get a new vaccine against the new flu.Predictors of taking preventive measures and strong intention to comply with measures regarding Influenza
A (H1N1) (Continued)

Perceived self-efficacy
(summary score)

low self-efficacy
31.3 1.00
1.00
18.4 1.00
1.00

high self-efficacy
48.6 2.08 1.59-2.72 <0.001 1.68 1.26-2.22 <0.001 86.3 27.9 19.5-39.8 <0.001 21.53 14.70-
31.55

<0.001

Maladaptive response
(summary score)

Underestimation
statements

(fully) disagree/not
disagree-agree (1-
3)

43.0 1.00
56.5 1.00

(fully) agree (4-5)
33.4 0.67 0.51-0.87 0.003
-
-
-
38.2 0.48 0.36-0.62 <0.001
-
-
-

Fatalism
statements

(fully) disagree/not
disagree-agree (1-
3)

43.3 1.00
57.1 1.00

(fully) agree (4-5)
34.1 0.68 0.52-0.89 0.004
-
-
-
39.5 0.49 0.38-0.64 <0.001
-
-
-
Avoidance
statements
(fully) disagree/not
disagree-agree (1-
3)

34.6 1.00
1.00
45.7 1.00

(fully) agree (4-5)
46.2 1.63 1.24-2.13 <0.001 1.43 1.07-1.90
0.02
54.3 1.41 1.08-1.84
0.01
-
-
-

Amount of
information received

nothing/little/
some (1-3)

33.2 1.00
46.2 1.00

much/very much
(4-5)

44.8 1.64 1.25-2.13 <0.001
-
-
-
51.8 1.25 0.97-1.62
0.09
-
-
-

Attention paid to the
information

(very) little/some
(1-3)

33.1 1.00
1.00
44.4 1.00

much/very much
(4-5)

61.3 3.19 2.31-4.40 <0.001 2.36 1.67-3.33 <0.001 66.7 2.51 1.81-3.47 <0.001
-
-
-

Reliability of
governmental
information

not (at all)/little
reliable (1-3)

36.0 1.00
39.8 1.00
1.00

(very) reliable (4-5) 42.7 1.33 1.02-1.73
0.04
-
-
-
59.9 2.26 1.74-2.94 <0.001 1.74 1.19-2.55
0.004

Sufficiency of
governmental
information

not (at all)/little
sufficient (1-3)

36.8 1.00
46.2 1.00

(very) sufficient (4-
5)

41.5 1.22 0.94-1.59
0.1
-
-
-
52.0 1.26 0.97-1.63
0.08
-
-
-

R 2
0.14
0.60

The increase in perceived vulnerability and number of individuals taking preventive measures may be an effect of the increasing number of Influenza A (H1N1) infected cases, including the first fatal case in The Netherlands in August 2009. Previous studies showed a similar effect. For instance with the inclining phase of the SARS outbreak in 2003, the prevalence of wearing a face mask and adopting better hand hygiene increased dramatically when the number of SARS cases increased[39]. During the current study period, there was no official recommendation from the Dutch government to take preventive measures; the government was in the process of preparing a national information campaign called 'Fight the flu'. This campaign was launched at the end of August 2009, and included announcements on television and a leaflet which was sent to every home in the country providing information about what people can do to prevent themselves and others. So, at the moment of the third data collection period the government had not yet actively informed the general public about preventive measures.
Bults et al. BMC Public Health 2011, 11:2 http://www.biomedcentral.com/1471-2458/11/2 Page 3 of 13
Erasmus MC, University Medical Center Rotterdam, Department of Public Health, P.O. Box 2040, 3000 CA Rotterdam, The Netherlands.
AcknowledgementsThis study was supported by the Netherlands Organisation for Health Research and Development (ZonMw). The majority of ZonMw' s commission comes from the Ministry of Health and the Netherlands Organisation for Scientific Research. The authors would thank the members of the Flycatcher Internet panel for their participation in this study, Pleun Aardening of Flycatcher Internet Research for his help during the data collection process and Caspar Looman of Erasmus MC for his advice in data analyses.Authors' contributionsAll authors contributed to the study design. MB, DB, and HV played a main role in the data collection process. Data analysis was performed by MB and HV with advice of PvE. MB, DB, OdZ, and HV wrote the first draft of the manuscript; GK, PvE, JvS, and JHR critiqued the manuscript and contributed to further drafts. HV is the guarantor. All authors read and approved the final manuscript.Competing interestsThe authors declare that they have no competing interests.
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Novel dual-function CellDetect® staining technology: wedding morphology and tinctorial discrimination to detect cervical neoplasia

Pavel Idelevich
Adi Elkeles
Elimelech Okon
Don Kristt
Dov Terkieltaub
Ilia Rivkin
Ilan Bruchim
Ami Fishman
Novel dual-function CellDetect® staining technology: wedding morphology and tinctorial discrimination to detect cervical neoplasia
R E S E A R C H Open Access
Background: A persistent goal of oncologic histochemistry is to microscopically identify neoplasia tinctorially. Consequently, the newly developed CellDetect® staining technology, that appears to exhibit this property, warrants clinical evaluation. The objective of this study was to compare the diagnostic results using CellDetect® to the outcomes of standard microscopic examination based on hematoxylin and eosin (H&E) staining for the recognition of different squamous epithelial phenotypes of the uterine cervix. Methods: Pairs of adjacent sections were made from 60 cervical biopsy cases that were diagnosed originally as either normal or neoplastic (CIN, SCC). One section of the pair was stained for H&E; the second section, with CellDetect®. Based on the examination of these pairs by two experienced pathologists, we investigated the following issues:(1) diagnostic agreement between the pathologists on each pair; (2) agreement between H&E and CellDetect® for each pair (3) tinctorial characteristics in micro-regions (n = 130) evaluated as either normal, reactive or neoplastic. Results: Qualitatively, CellDetect®-stained preparations displayed cyto-morphological detail comparable to H&E images. Tinctorially, non-neoplastic cells appeared green/blue when stained withCellDetect®, contrasting with cytologically neoplastic foci, where cells of every grade were red/magenta in color. Due to these tinctorial characteristics, even small foci of neoplasia could be readily distinguished that were inconspicuous on H&E at low magnification. In some instances, this prompted re-examination of the H&E and revision of the diagnosis. Quantitatively, we found that despite diagnostic variation between pathologists, in about 3% of the cases, each pathologist made the same diagnosis regardless of whether CellDetect® or H&E was used, i.e. there was 100% selfagreement for each pathologist between stains. Particularly noteworthy was the finding of a 0% false negative rate, coupled with a 10-15% false positive rate. Regarding specificity, the performance in reactive squamous processes was similar to that observed for morphologically normal squamous epithelium.Conclusions: In this first order assessment of clinical applicability, CellDetect® staining technology was at least comparable to results using H&E, and perhaps surperior. CellDetect® provided a uniquely useful tinctorial clue for the detection of neoplasia, which exhibited an impressive 0% false negative rate. A more extensive, blinded study is needed to confirm these promising findings.

Background

Although cervical cancer is still one of the major sources of mortality in women, advances have been made in combating this disease by early detection and diagnosis [1]. Cytological screening programs that triage suspicious epithelial changes for subsequent definitive biopsy have had a significant impact on achieving improved therapeutic outcomes. Nonetheless, an assessment of cell or tissue morphology alone may be inadequate to detect early indications of neoplasia in some cases. Due to this limitation of a solely histological approach, a range of histochemical, immunocytochemical, and molecular biological approaches have been used as adjuncts to standard microscopy [2,3]. The latter methods add information on the unique cell biology believed to distinguish a neoplastic phenotype [2,4]. However, these adjuncts are not generally informative on all, or even most, neoplastic conditions. We thus remain challenged to find a universal light microscopic diagnostic tool for neoplasia, particularly for recognition of in situ, pre-malignant states that represent the most urgent goal of early detection programs.

Recently, Zetiq Technologies Ltd. introduced a new morpho-histochemical stain for neoplasia, named Cell-Detect®. This staining technology has been shown to consistently differentiate cancer from normal tissues and reactive states in histological and cytological preparations, as well as cultured cell lines [5,6]. In such stained preparations, the cytoplasm of normal cells is greenblue, whereas the cytoplasm of neoplastic elements is distinctively pink-red or magenta. These differences can be objectively demonstrated using optical instruments that discriminate wavelength [5]. Importantly, the morphological characteristics of cells stained with CellDe-tect® are preserved, allowing the application of standard, microscopic diagnostic criteria as well. This background suggested that CellDetect® might serve as a useful adjunct in clinical applications, since it offers the morphological resolution capabilities of hematoxylin and eosin (H&E) staining, while providing an additional histochemical dimension for the diagnosis of neoplasia.

Consequently, we undertook this first-order, non-blinded evaluation of CellDetect®'s performance in assessing cervical epithelial neoplasia. Towards this end, the CellDetect® stain was applied to a series of clinical samples representing different phenotypic states of the cervical squamous epithelium, from normal to invasive SCC. The diagnosis made on each CellDetect®-stained section was compared to the results on an adjacent section stained with standard H&E. In order to avoid confounding errors due to intraobserver variability, each pair of slides from all cases was independently assessed by two pathologists. We found that the diagnostic results using CellDetect® were completely comparable to H&E. In one regard CellDetect® staining was superior because the tinctorial characteristics preferentially facilitated judging the grade of intra-epithelial neoplasia microscopically, even at low magnification.

Methods

This was a single-center, non-blinded study using 60 archival cervical biopsy cases with the following diagnoses: normal, 22 cases; CIN-2/3, 18 cases; squamous cell carcinoma, 20 cases. To assess the staining in morphologically reactive processes, 12 micro-regions (see below), in these cases, were specifically examined.

All cases were diagnostically re-evaluated using two new adjacent sections that were cut from a single paraffin block representative of each case. One of these two sections was stained by the standard H&E procedure, and the other by the CellDetect® method. All of these pairs of stained slides were reviewed by two pathologists, independently; their diagnostic conclusions for each case were compared in regard to: (1) the two stains as a function of diagnosis and (2) inter-observer agreement for diagnosis in each case.

Staining Protocols Hematoxylin/Eosin Staining Protocol

Paraffin-embedded tissue samples were sectioned at 4 microns, and mounted on standard microscopic slides. Deparaffinization was accomplished as follows: immersions in xylene, twice (3 min each); 100% ethanol, twice (3 min each); immersion in 95% ethanol, twice (3 min each); distilled water (3 min). These sections were stained with hematoxylin, Dye-1, (1 min), washed in tap water until the water was clear. Sections were stained in eosin, Dye-C, (1-2 min) and washed in tap water, as above. For cover-slipping, the sections were dehydrated in an ascending series of ethanol concentrations (50%, 70%, 80%, 95% × 2, 100% × 2), cleared in xylene (3 -4 times), and then mounted in Permount, or an equivalent commercial product.

CellDetect® Staining Protocol

The staining was performed according to the manufacturer's instructions. Although the details of the protocol and the formulation of the stains are currently proprietary information, the kits contain three ingredients: (1) an acidophilic red stain, (2) a basophilic green stain, and (3) a proprietary plant extract necessary for the specific reaction. The six-step staining protocol was completed in approximately 30 min.

Slide Evaluation

This was made in two stages.

(1) Comparison of observer performance: Each of the two experienced pathologists examined each case with both stains, and made two observations. First, an overall diagnosis on a case was made. Second, they recorded whether their own diagnostic impression on the H&E was in agreement with their impression based on the CellDetect®-stained slide.

(2) Comparison of individual micro-regions: Morphological versus tinctorial performance of CellDetect® relative to H&E, was assessed in multiple, small regions within each of the 60 biopsies that exhibited a uniform histological phenotype. These are referred to as: micro-regions. Since the regional variation along the squamous epithelium in each case ranged from normal, CIN or SCC, multiple morphologically distinct regions were present in most cases. The total number of regions was 130. For each region, a single pathologist first assessed the morphology using H&E. Then independently, the same region was examined in the adjacent section stained with CellDetect®. Thus two morphological diagnoses were made on each region, which were compared to the tinctorial characteristics in CellDetect® of each site.

Results

Qualitative features of CellDetect® staining

Normal cervical squamous epithelium and reactive processes of squamous epithelium (see below) stain green/ blue ( Figure 1). In contrast, morphologically recognizable neoplastic cells in CellDetect®-stained preparations always exhibited red/magenta tinged cytoplasm ( Figure  2A, C, E). Thus, it was possible to recognize neoplasia, even at low magnification, based exclusively on tinctorial status of the epithelium (Figure 2A, C). Similarly, staining with CellDetect® highlighted the patchy distribution of CIN along the epithelium, a feature we exploited for another aspect of the analysis, considered below. The tinctorial aspects of the histology also clearly demarcated the laminar patterning that is so characteristic of intra-epithelial neoplasia (Fig 2A). Importantly, such color-based impressions were readily confirmed at higher magnification using the same preparation. This could be accomplished because the CellDetect® stain preserved critical diagnostic cytological features of neoplasia evident in the red-stained cells ( Figure 2E).

Quantitative diagnostic performance of CellDetect®

Three aspects of diagnostic performance were assessed: (1) diagnostic agreement between the pathologists on each case; (2) the agreement between H&E and CellDe-tect® for each case, for each pathologist. (3) Micro-regional evaluations directly comparing morphological performance (H&E, CellDetect®) with tinctorial characteristics of the same cell populations.

Inter-observer variation for case diagnosis

The final diagnosis rendered on each case by each pathologist, using both stains together, was different in 2 cases (~3%) cases (Table 1). These discrepancies were not related to stain used, as documented in the next section.

Within-observer results between stains

In contrast to the foregoing, each pathologist was entirely consistent across stains, so that no discrepancy between H&E and CellDetect® was noted in any case (Table 1), i.e. each pathologist demonstrated a 100% inter-stain concordance. These data served as a validation, enabling a more detailed assessment of the correlations between morphological and tinctorial diagnosis, as explained in the following sections. Despite this final outcome, CellDetect® highlighted inconspicuous neoplasia in three cases that had initially been overlooked, thus prompting a re-examination of the H&E and revision of the diagnosis according to the CellDetect® findings.

Morphology vs. tinctorial characteristics in neoplastic micro-regions

To more critically compare the performance of CellDetect and H&E, the inherent variation of epithelial phenotype often seen in cervical biopsies samples was utilized. A series of 130 microscopic regions with homogeneous phenotype, culled from the 60 cases, was examined by a single pathologist. The pathologist first diagnosed the focus as either normal, CIN or SCC based on H&E. Subsequently, the same area was identified morphologically in the CellDetect® slide, and the tinctorially features  were recorded. In all cases of CIN or SCC, cells stained pink/red, so that the false negative rate was 0%. In contrast, loci considered morphologically normal in both H&E and CellDetect®, stained green/blue in approximately 90% of cases, i.e. a 10% false positive rate was observed. Table 2 shows the breakdown of the morphological status of each micro-region and the accompanying histochemical results. For each micro-region, staining color was recorded for morphologically normal and atypical cells. By definition, normal cells were not found in CIN3 or SCC micro-regions, and atypical cells were not noted in morphologically normal microregions.

It is important to note, that although Table 2 lists micro-regions of CIN1, these were incidentally present in cases actually diagnosed as CIN2/3. CIN1 was recognized based on accepted cytological criteria including nuclear atypia and koilocytosis. Since CIN1 is characterized by atypical squamous cells confined to the lower one third of the epithelium, the red staining from Cell-Detect® was limited to the same extent. Morphology vs. Tinctorial characteristics in reactive micro-regions To examine the specificity of the histochemical staining reaction to neoplasia, micro-regions were chosen with morphological characteristics on H&E of either inflammation or squamous metaplasia. Table 3 summarizes these observations, and provides the data on normal cells (derived from Table 2), for comparison. It can be seen that the majority of micro-regions with any of these diagnoses was most likely to be green stained. The small percentage of red-stained cells among cells exhibiting squamous metaplasia is similar to their incidence in morphologically normal squamous epithelium.

Discussion

This work represents the results of a first order clinical assessment of the new dual-function CellDetect® method. This technological approach claims to tinctorially discriminate neoplastic cells while preserving morphology [5]. Using these morphological capabilities, in conjunction with H&E, cytologically neoplastic cells uniformly exhibited a neoplastic histochemical phenotype with red/pink cytoplasm, i.e. providing a zero false negative rate.

In contrast, some false positive staining occurs. We found that 10-15% of morphologically normal squamous cell foci had cells that stained red/pink, instead of the expected green/blue. On one hand, this raises the exciting possibility that the CellDetect® method is detecting pre-neoplastic changes, heralded at this early stage by some, yet to be defined, metabolic alteration (see below). On the other hand, it is still possible that an artifactual, red staining reaction may occur in some normal cells. In any event, the low level of this phenomenon should not affect the application of CellDetect® to routine diagnostic pathology because it will merely prompt a re-examination of the morphology in such false positive instances.

Another significant implication of this phenomenon is that the same frequency of red-staining micro-regions was seen in metaplastic and inflammatory squamous settings. Although relatively few of such cases were available, the congruence of the findings with the larger sample of normal loci supports the likelihood that these conditions will usually stain differentially as normal tissue, suggesting a high level of specificity of the technology for neoplasia. Naturally, all of these novel findings need to be substantiated in a larger, blinded investigation, which will also include the evaluation of additional benign conditions such as atrophy and immature squamous metaplasia.

From a qualitative perspective, it is worth underscoring that CellDetect®, proved particularly useful because the expression of cervical intra-epithelial neoplasia (CIN) is often spotty, and all foci may not be uniform in   grade. Indeed, small foci of CIN were occasionally overlooked by our two experienced pathologists using the standard hematoxylin-eosin stained preparations. Cell-Detect® staining detected neoplasia in these cases. This prompted re-examination of the H&E and revision of the diagnosis, thus confirming the heightened detection sensitivity of the CellDetect® technology. We suspect that the basis for this superior sensitivity is entirely visual. The process of CIN is expressed as a laminar cellular change in the epithelium. CellDetect® staining highlights these changes by forming an intra-epithelial tangential reddish band. The latter is easily seen even at low magnification. The finding of a~3% variation in case diagnosis, between the two experienced pathologists, is attributed to well known factors. These include differences in diagnostic criteria for a given grade of neoplasia, or threshold for the diagnosis of neoplasia over normal [7][8][9][10][11]. What is critical to note here is that these differences of opinion were not influenced by the stain used; H&E and CellDetect® had the same outcomes for each observer.

In short, the findings indicate the likelihood that Cell-Detect® preparations will continue to prove as useful as H&E, and perhaps ultimately, superior because CellDe-tect® provides both morphological and tinctorial information that are diagnostically relevant.

Given the success of the CellDetect® technology, it is of interest to consider how its performance compares to other cellular markers for cervical neoplasia. For instance, one alternative approach is based on immunocytochemical detection of cellular proteins, such as p53, p16 or HPV viral antigens [12][13][14][15]. Reports using these markers show that although the marker may be expressed in all grades of cervical neoplasia, in some cases, a particular grade may exhibit no demonstrable expression. That is to say, cells and epithelia satisfying morphological criteria for neoplasia fail to demonstrate the target antigen. In contrast, squamous cells with neoplastic cytology always stained appropriately using Cell-Detect®. An additional complication has been reported regarding the popular p16 (INK4a) in that this marker protein may be demonstrable even in cytologically normal cells [14]. A similar occurrence was found in Cell-Detect® preparations, but its low incidence should not impact on routine diagnostics, as discussed earlier.

Due to the dramatic, bi-polar histochemical cytoplasmic reaction produced by CellDetect® -red or green -the question of possible mechanism arises. These observations prompt the speculation that the staining phenomenon reflects fundamental shifts in cell structure and function that underlie the transformation from normal/reactive states to neoplasia. For instance, most malignancies characteristically exhibit alternations in metabolic state [16][17][18], level of differentiation and rates of proliferation [19]. Our previous work suggested a relationship between staining outcome and differentiation. In that study [5], forced differentiation of malignant cell lines uniformly converted the red/magenta cytoplasmic staining to green, as we would anticipate. On the other hand, proliferation of phenotypically benign cells does not alter staining. The latter is exemplified by the proliferative basal cell layer, which always exhibits a non-neoplastic histochemical phenotype, viz. green cytoplasm. Although these observations are provocative, a more direct examination of these issues will be required before any mechanistic option can be accepted.

Conclusions

In conclusion, the findings in this non-blinded study substantially support the claim that CellDetect® can tinctorially discriminate neoplastic cells while preserving morphology [5], at least for cervical neoplasia. Despite interpretative limitations imposed by a non-blinded experimental design, the outcomes using different strategies for comparison of morphology and tinctorial qualities, were entirely consistent throughout the study Clearly, these initial observations are promising, but they need to be cautiously assessed, and bolstered by a more extensive, prospective evaluation.

Figure 1
1CellDetect® and H&E staining of normal cervical epithelium. Using CellDetect® normal epithelial cells stain green/blue.

Figure 2
2CellDetect® (A, C, E)and H&E (B, D, F) staining of neoplastic cervical epithelium. CellDetect® stained neoplastic cells red/magenta, at every grade. (A) CellDetect® staining of low-intermediate grade CIN. Note that the red staining neoplasia was conspicuously laminar, a feature facilitating grading even at low magnification. (B) H&E-stained section adjacent to A. (C) CellDetect® staining of high grade CIN. (D) H&E-stained section adjacent to C. (E) CellDetect® staining of high grade CIN seen at higher magnification than C, to illustrate details of cell morphology. (F) H&E-stained section adjacent to E.

Table 1
1Comparison of Pathologists' assessment using H&E and CellDetect®Pathol #1
Pathol #2

Diagnosis
H&E
CD
H&E
CD

Normal
21/60*
21/60*
22/60
22/60

CIN
22/60
22/60
22/60
22/60

SCC
17/60
17/60
16/60
16/60

Table 2
2Relation of neoplastic morphology to
histochemical results

Dx
n
Normal
Atypical

Green
Red
Green
Red

Normal
47
89%
11%
-
-

CIN 1*
6
100%
0%
0%
100%

CIN 2
17
88%
12%
0%
100%

CIN 3
23
-
-
0%
100%

SCC
37
-
-
0%
100%

Total
130

n, number of micro-regions with diagnosis
* CIN1 fields were found in cases diagnosed as CIN2/3

Table 3
3Relation of reactive morphology to histochemical resultsDx
n
Green
Red

Normal
47
89%
11%

Inflammation
5
100%
0%

Metaplasia
7
86%
14%

Total
59

Abbreviations CIN: Cervical intraepithelial neoplasia; SCC: Squamous cell carcinoma; H&E: haematoxylin and eosin stain; HPV: human papillomavirus. Dr. Adi Elkeles Dr. Elkeles holds a PhD from Tel Aviv University, an MBA from the College of Management, and completed a three-year post-doctoral fellowship in Molecular Cell Biology at the Weizmann Institute of Science. An alumni of the Paul Merage life science executive leadership program at UC Irvine California, U.S.A, Dr. Elkeles is an experienced executive in the biotech field, specializing in biopharmaceutical development. Dr. Elkeles has significant research and development experience in various fields of biology including cancer, immunology and infectious diseases. Prior to joining Zetiq, Dr. Elkeles served as Drug Development Manager for BiolineRx and as manager at XTL Biopharmaceuticals. Prof. Elimelech Okon Prof. Okon is a Clinical professor of Pathology Emeritus at the Sackler School of Medicine, Tel Aviv University. He served as the Chairman of the department of Pathology at Rabin Medical Center between 1996 and 2008. Since 2009, he is the Medical Director at LEM laboratories, Israel. Prof. Don Kristt Dr. Kristt is head of Molecular Pathology Unit at the Rabin Medical Center and an adjunct professor at Bar Ilan University. As a physician experienced in both clinical and experimental pathology, he has made important contributions in the fields of histochemistry, electron microscopy, molecular pathology and transplantation medicine. In the past he has been a Professor at Johns Hopkins MC, Stanford MC and the University of Maryland. Mr. Dov Terkieltaub A graduate of Bar Ilan University, Dov has extensive experience in product development. A veteran of 18 years in the Biotech field, Dov has managed the development of many products, assays and processes. Experienced in project management, he has brought a number of products from bench to bedside. Prior to joining Zetiq, Dov served at Interpharm ltd (a Serono company) in QC and development, and held managerial positions at XTL Biopharmaceuticals and Intelect Neurosciences. Mr. Ilia Rivkin A PhD student at Tel Aviv University, Ilia holds an M. Sc. in Biochemistry from Tel Aviv University and B.Sc. in Biotechnology from Braude Academic College of Engineering. Mr. Rivkin has research and practical experience in fields of chemistry and biotechnology including cell-based assay development, HTS robotic automatization and establishing of drug-carrier systems for cancer treatment. Dr. Ilan Bruchim A graduate from Faculty of Medicine, Technion, Haifa, Dr. Bruchim completed his residency in Obstetrics & Gynecology at Meir Medical Center, Kfar-Saba, Israel and a fellowship in Gynecologic Oncology at McGill University, Montreal, Canada. He is currently a faculty member of Gynecologic Oncology Unit, Department of Obstetrics & Gynecology, Meir Medical Center, Kfar-Saba, affiliated with the Sackler School of Medicine, Tel Aviv University. Prof. Ami Fishman Graduated from the Faculty of Medicine, Tel-Aviv University. Prof. Fishman completed his residency in Obstetrics & Gynecology at Rambam Medical Center, Haifa, Israel and fellowship in Gynecologic Oncology at Baylor College of Medicine, Houston, TX. In his current position, Prof. Fishman is the Chairman of the Department of Obstetrics & Gynecology, Meir Medical Center, Kfar-Saba, affiliated with the Sackler School of Medicine, Tel-Aviv University, Israel. interests Among the authors, Pavel Idelevich, Adi Elkeles, Dov Terkieltaub and Ilia Rivkin are employees of Zetiq; Elimelech Okon, Don Kristt, Ami Fishman are paid consultants.Competing
Idelevich et al. Diagnostic Pathology 2010, 5:70 http://www.diagnosticpathology.org/content/5/1/70 Page 2 of 7
AcknowledgementsWe wish to thank the LEM Pathology Laboratory (Nes-Ziona, Israel) for technical assistance.
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