Adolescents Searching for Health Information on the Internet: An Observational Study

Background Adolescents' access to health information on the Internet is partly a function of their ability to search for and find answers to their health-related questions. Adolescents may have unique health and computer literacy needs. Although many surveys, interviews, and focus groups have been utilized to understand the information-seeking and information-retrieval behavior of adolescents looking for health information online, we were unable to locate observations of individual adolescents that have been conducted in this context.
Introduction
The Internet has become an important tool for many people with health concerns [1,2], especially for adolescents [3,4]. Concerns about confidentiality, coupled with the fact that many teenagers find accessing care through traditional providers difficult [5], make access to information via the Internet particularly important. Given rapidly-expanding Internet access among young people, it is not surprising, then, that more than 70% of 15 to 17 year-olds say they have used the Internet to look up health information (written communication, 2001 Dec; Generation RX.com Survey printouts; V. Rideout, Henry J. Kaiser Foundation, Menlo Park, CA). This percentage is likely to increase if Internet access from home continues to rise as it has in recent years [6].
Because of the enormous amount of unstructured online content, it is crucial to understand how youth navigate through the Web to find health information. Prior research, primarily from library and information science literature and education literature, has highlighted several search characteristics that are either unique or more pronounced in adolescents. For example, adolescents take more time to complete online tasks than college students [7], search less systematically [7- 10], have difficulty formulating search queries due to misspelling and problems with the level of specificity [8- 11], utilize less-advanced search syntax [7], and rarely consider the source of Web pages [8,9]. While informative, this literature is based primarily on adolescents searching for answers to homework questions rather than health information.
Searching for online health information involves distinctive challenges including unfamiliar terminology [12]; encounters with pornography-blocking software (written communication, 2001 Dec; Generation RX.com Survey printouts; V. Rideout, Henry J. Kaiser Foundation, Menlo Park, CA), [13]; and the importance and difficulty of determining health information quality [14]. However, despite the need for research that details the online search behavior of health consumers, the authors were only able to locate a few articles in which health science researchers actually observed, recorded, and analyzed consumers of any age searching for health information [14- 16]. Instead, surveys (eg, written communication, 2001 Dec; Generation RX.com Survey printouts; V. Rideout, Henry J. Kaiser Foundation, Menlo Park, CA; and [1,2,4]) have been the predominant method used to understand health consumers' online searching behavior, despite problems with participant recall and the inability of surveys to capture specific search tactics. In addition, the authors found a handful of studies in the medical informatics literature that have also looked at log data from particular medical Web sites, but these studies are also limited in scope since they do not observe the actual searcher or see the broader context in which the searcher is acting [17] (see also [18] for similar studies performed on search engine data). The value of directly observing users was demonstrated in the Eysenbach study, which revealed that adults said they paid attention to the source of health sites during interviews, although this behavior was not found during the actual observations [15].
Observational research specific to the adolescent age group and online search behavior for health information is also sparse. There have been some good surveys that answer many useful questions concerning why adolescents go to the Internet, what they search for, if they find it, and what they do with it (written communication, 2001 Dec; Generation RX.com Survey printouts; V. Rideout, Henry J. Kaiser Foundation, Menlo Park, CA;and [4,19]). The only observational study we were able to locate conducted 27 focus groups where groups of adolescents searched online for health information as they discussed their own experiences [14]. Many of the findings concerning adolescent search behavior found in the library and information science literature were confirmed and additional issues were raised, including concerns about low health literacy and trouble judging the quality of information, that may be more pronounced in adolescents than adults. However, that study only begins to paint a picture of adolescent search behavior for online health information, because the searches were performed in a group setting and the success, failure, and specific search tactics used were not coded or analyzed.
The study reported here provides a more in-depth understanding of how adolescents search for health information using the Internet and what implications this may have on access to health information. To capture enough detail, the study recorded specific actions taken by adolescents which were later coded and analyzed. Participants were encouraged to share their thought process out loud as they searched for answers to a list of predetermined health questions. The result was a rich set of both quantitative and qualitative data that was thoroughly analyzed for common themes and events. Specific questions of interest include, but are not limited to: What are the various search strategies used? What factors contribute to finding correct and useful answers? When using a search engine, how many results pages are viewed and utilized? What types of search strings are entered into search engines? Answers to these and related questions should be of interest to a number of parties including educators (eg, health educators, librarians, teachers), Web site and search engine designers, health care practitioners, and researchers (eg, to create a sample of URLs by simulating online searching behavior [20]).
Methods
Sample
Twelve students from 1 middle school (N= 4) and 2 high schools (N = 4 and N= 4) in southeast Michigan were recruited for this study. Staff at each school were asked to select 4 students who were (a) comfortable using computers, (b) comfortable searching for information on the Internet, and (c) strong students who could afford to miss one class period. Students received a University of Michigan T-shirt, valued at roughly $8, in return for their participation.
The parent or guardian of every student signed an informed consent document that described the purpose and procedure of the study. Students also signed separate assent forms with similar information. The University of Michigan Behavioral Science Institutional Review Board approved this study and the consent and assent documents.
Data Collection
Three methods of data collection were used. First, one of the two members of the research team present during each of the observations coded searching behavior in real time while the second member of the research team interacted with the student. Second, TechSmith Camtasia 3.0.1 commercial tracking software [21] was installed on the computer. This software captured the students' voices and took pictures of the screen (screen captures) twice per second during the entire session. Finally, a video camera was positioned to capture the screen and the students' voices, but not the students' images. Observations coded in real time were used to develop a more detailed and systematic coding system for use when reviewing the tracking software records. It is data from the tracking software coding that is reported here.
All observations of adolescents were conducted during January 2002. Each school provided a room in which to conduct the observations. Students were brought to the observation room one at a time. Two researchers were present at every observation. For each student, one of the researchers first reviewed the assent form to introduce the project and obtain the student's permission to participate. The students were then asked 14 questions about demographics (age, race/ethnicity, and gender) and their prior computer use (eg, how often they use computers or the Internet, what health topics they have searched, which search engines they used, and whether they have a computer and access to the Internet at home).
Once the brief interview had been completed, the observed searches began. To help the students understand the procedure and to reinforce the importance of thinking out loud while doing their searches, each student was first asked to do an easy non-health-related search looking for the next day's local weather forecast. As with the subsequent health-related searches, the local-weather question was first read to the student by a researcher and then a card with the question on it was set next to the computer in case the student needed to read it. As part of the think-aloud protocol, the experimenter asked the student to talk out loud about what they were doing, so that researchers could better understand the reasons behind the searching behavior. If a student stopped talking during the search, he or she was reminded by the observers to "keep talking," but the experimenters did not ask students to elaborate on any specific thing they said. Concurrent verbal reports more accurately reflect a subject's mental state at the time of observed behaviors than do retrospective reflections, and this minimal think-aloud protocol has been shown to slow subjects down, but not to qualitatively change their problem solving behavior [22].
After the students completed the practice local-weather search, they were given a sequence of up to 6 predetermined health information questions (see Table 1), 1 at a time. Questions were framed in a way that took into consideration the broader information concern that the question attempted to resolve. To eliminate confounding by learning effects between searches, we used a 6 x 6 Latin square to determine the order in which the questions were presented to the participants. The computer that students used was provided by the researchers, but connected to the school's network so that the students were protected from controversial or pornographic material by the same blocking or filtering software used by the school. The 3 different schools used 3 different filtering systems. Each observation session lasted one class period. No time limit was given for each question, but when the class period ended, any ongoing search was terminated and any remaining questions were skipped.
Table 1
Health-related questions
Your aunt was just told she has diabetes. She isn't sure what kinds of food she can or can't eat. Using the Internet, find some information for your aunt about what foods she should or should not eat.
A friend recently started taking a drug called Paxil for depression. He seems to be tired all the time, and even falls asleep in class. Use the Internet to find out if the drug might be making him sleepy.
Your older brother has a problem with drinking too much alcohol. He wants to go to a local Alcoholics Anonymous meeting. Use the Internet to help him find a local meeting.
You want to get an HIV test, but you don't want anyone to know. You also don't have any money to pay for it. Use the Internet to find a place to get a free and confidential HIV test.
For class, you need to learn about medicine that can help people stop smoking. Using the Internet, find the names of these medicines.
You are about to get a tattoo, but a friend warned you that some places spread infections like HIV and hepatitis. Use the Internet to find out if this is true.
Topics for the health-related questions were chosen based upon responses to a survey of adolescents conducted by the Kaiser Family Foundation (written communication, 2001 Dec; Generation RX.com Survey printouts; V. Rideout, Henry J. Kaiser Foundation, Menlo Park, CA). Certain topics including homosexuality, teen pregnancy, and abortion were purposefully avoided so as not to expose participants to overly-controversial information.
Data Analysis
After all the observations were completed, 3 researchers including a physician, health educator, and human-computer interface specialist met as a group to review the real-time coding results and to clarify or augment the coding scheme before the definitive final coding of the tracking-software records. The final coding scheme was designed to record data on the person searching, the question being asked, the time it took to find an answer, the search strategy utilized (eg, utilize search engine or directly type in URL); search strings used; number of search engine results pages reviewed; number of pages viewed within a particular site; and the use of menus, advertisements, and directories. One of the 3 coders was assigned as a primary reviewer for each of the observation sessions. The assigned primary reviewer was responsible for a detailed coding of the observation session and any coding problems were resolved in a second group discussion.
The reviewers classified each of the answers found by the students as correct or incorrect, complete or incomplete, and, for location questions only, useful or not
useful. To avoid being overly narrow in our classification of correct for the more open-ended questions such as the question on healthy foods for a person with diabetes, we used the following general rule for classification: to be considered correct, the content of the answer had to be the kind of information that might be discussed in a medical school or school of public health. This classification system was validated in previously-published work by the research team and resulted in a high inter-rater reliability (κ = 0.84) [13]. The more-specific questions such as the question asking about a location for an Alcoholics Anonymous meeting were considered correct if the student found a Web page listing a meeting location and time or contact phone number. Answers were complete if the students were able to answer all parts of the question. For example, if the student found a discussion about HIV transmission by tattoo parlors, but did not find an answer about hepatitis it was classified as incomplete. Useful answers pertained to location questions. An Alcoholics Anonymous meeting in another state was not useful. A summary measure classifying each search as successful, partially successful, or unsuccessful was computed using the correct, complete, and useful ratings. To obtain a rating of successful, the answer had to be complete, correct, and useful. If the student gave up before finding an answer, the search was classified as unsuccessful.
Results
Twelve middle school students and high school students in southeast Michigan participated. Students ranged in age from 12 to 17 years old, with a mean of 14 years. Half of the students were female. Of the 12 students, 7 were white, 2 were African American, 1 was Indian American, 1 was Hispanic, and 1 was Asian American. Of the 12 students, only the 6 oldest students had searched for health information on the Internet before. The variation by age is consistent with other findings that youth age 15 to 17 years are significantly more likely to have looked up health information (32%) than youth age 12 to 14 years (18%) [23]. All of the students, however, had computers and access to the Internet at home. Students reported using a computer from 1 hour per week to 3 hours per day, with a mean of 12.3 hours per week.
Eleven students attempted all 6 searches, while the remaining student attempted 3, for a total of 69 searches. One search was not included since the Internet connection was not working properly, making a total of 68 searches that were analyzed. Searches took an average of 5 minutes and 41 seconds, ranging from just under a minute to nearly 24 minutes. This time frame is essentially the same as Eysenbach recorded for adults [15]. Although direct comparison is inappropriate since different questions were asked, the similar order of magnitude is suggestive.
Overall Search Strategy
As students thought aloud, the researchers got a sense of what students were looking at on each page. Students seemed to skip around a lot, and didn't skim results pages or specific Web sites in any methodical or thorough ways, sometimes missing links or text that contained the answer to questions. This is also consistent with findings from non-health-related searching behavior as summarized in Hsieh-Yee [24].
Table 2
Distribution of pages viewed per site
Pages Viewed Per Site
Sites
n
%
Cumulative %
1
143
70.4
70.4
2
27
13.3
83.7
3
11
5.4
89.2
4
8
3.9
93.1
5
8
3.9
97.0
6
2
1.0
98.0
8
1
0.5
98.5
9
1
0.5
99.0
15
2
1.0
100.0
Total
203
100
Students used multiple methods to locate Web sites that they believed contained answers to the 68 questions. In 60 cases, the student started looking for an answer by visiting a search engine and entering in a search term or phrase. In 2 cases, the student started by selecting from directory menus (eg, choosing the topic health). In 6 cases, the student started by entering a URL (other than a search engine) directly into the browser address bar. In total, there were 215 attempts to access non-search-engine or directory Web sites. Nearly all of these attempts were made by following a link from a search engine either after a search or through the use of a directory. Of the 215 attempted site visits, 4 were broken links, 3 were blocked by the filters utilized at certain schools, and 5 were PDF files (read by Acrobat Reader) which students either could not download or chose not to download because downloading was too slow. This left 203 sites that were viewed with an average of 1.8 pages viewed per site. The distribution of pages visited per site is shown in Table 2. Note that the distribution is roughly consistent with a power law as observed in previous studies [25]. At a reviewer's request, this data was looked at on an individual student level. Students varied a great deal in the total number of visited sites. Eleven of the 12 students went only 1 page deep on the majority of visited sites. Although the individual-level data is not large enough to analyze more rigorously, the power law seems to operate on an individual level as well as the aggregate level.
Even when students found a Web site that contained the answer to a question, they did not always find the answer. One example is the Alcoholics Anonymous site [26] where 8 of the 11 students ended up while searching for a local meeting. Although there was a link to a site that contained local information, only 3 of the 8 students were able to find the link, 1 of whom only found it on the second visit to the Alcoholics Anonymous site, after viewing a total of 16 pages within the site. Similarly, 6 of the 11 students who searched for whether or not Paxil causes drowsiness visited the official Paxil site [27]. Only 3 of the 6 students were able to successfully answer the question based upon the information they found at the site. Two of them failed to find the list of side effects and 1 of them found the list but did not understand it enough (or read it carefully enough) to answer the question correctly.
Search Engine Tactics
Seven search engines were used, including 2 meta-search engines (Dogpile and Locate.com). The meta-search engine Locate.com offers the user a number of search engines to choose from. Searches performed from the Locate.com Web site that utilized another search engine (eg, Yahoo!) are reported as if the search occurred on the destination search engine (eg, Yahoo!). Table 3 summarizes the number of times that a particular search engine was used. If a search engine was used multiple times while searching for an answer to the same question, it is only counted once. Because students occasionally switched search engines while trying to answer the same question, there are more searches using a search engine (79) than there are attempts to answer questions (68). In total, 6 of the 12 students used only Google, 1 used only Yahoo!, and the remaining 5 changed search engines at some point.
Table 3
Search engine usage
Search Engine
Times Used
n
%
Google
38
48.1
Yahoo!
13
16.5
Ask
12
15.2
MSN
7
8.9
Hotbot
6
7.6
Dogpile
2
2.5
AltaVista
1
1.3
A total of 132 search phrases were entered into the various search engines. Only 104 of those search phrases were unique. The most-frequent 2 phrases used were "diabetes" and "Paxil," each of which had 5 occurrences. There was an average of 3.6 words typed in per search phrase and 80% of the time there were 4 or fewer words per search phrase.
Table 4
Distribution of search-result links viewed
Bands of Search-Result Links Viewed
Chosen Links
n
%
Cumulative %
Results 1-10
137
82.5
82.5
Results 11-20
8
4.8
87.3
Results 21-30
11
6.6
94.0
Results 31-40
4
2.4
96.4
Results 41-50
4
2.4
98.8
Results 51-60
1
0.6
99.4
Results 61 or more
1
0.6
100.0
Of the 132 search phrases, 30 contained at least 1 word that was misspelled (eg, "tatoo," "Alchoholics," or "smokeing"), despite the fact that students could read the correctly-spelled word on the index card containing the question. Some search engines (eg, Google) offer a feature that recommends an alternate search string with the correct spelling of a word. For example, if a student typed "alchoholics anonymous," the first page of results began with, "Do you mean 'alcoholics anonymous?'" Students were offered a new search string with correct spelling on 15 separate occasions, but only noticed and used it 6 times. The remainder of the times they used the results that were offered for the incorrect spelling. Of the 7 students who were offered corrected spelling suggestions, only 2 ever used them.
Once a search string was entered into a search engine, students varied in the number of results pages that were viewed. Students viewed only the first results page 78% of the time and 4 pages or less of results 93% of the time. Because search engines report a different number of links per page of search results, Table 4 reports how often links were selected from the first 10 results, the second 10, and so on. Only 3 blocked links were encountered during all of the searches, suggesting that blocking software did not have a significant impact on these results.
Successful Searching Characteristics
Of the 68 questions that students attempted to answer, 7 searches were abandoned after the student gave up or, in 2 cases, when the class period ended. Of the remaining 61 searches, 47 were successful in finding a complete, correct, and useful answer to the health question and the remaining 14 were unsuccessful. Six of the unsuccessful answers were completely incorrect and not useful, 4 were useful but only partially correct, and 4 were fully correct but not useful.
Several factors contributed to the success of finding a correct, complete, and useful answer. One important factor was the individual who was performing the search. Although every student answered at least 1 question correctly there was wide variation in the number of correct answers. Two students successfully answered 6 out of 6 questions, 3 students successfully answered 5 questions, 4 students successfully answered 4 questions, and the remaining 3 students only successfully answered 1 or 2 questions. While our sample of students was too small to draw conclusions from, no distinct patterns were observed that would indicate that race, gender, Internet experience, or health searching experience were significant determinants of success. However, the older adolescents (16-17 year olds) were successful 87% of the time (26 of 30) as compared to 68% (21 of 31) for the younger adolescents.
Another important factor was the difficulty level of the questions themselves. Table 5 shows the failure rate for each question. The 4 partially-correct answers were split evenly between the Alcoholics Anonymous and tattoo questions. All 4 of the correct but not useful answers resulted from the HIV test question.
Table 5
Unsuccessful searches by search topic
Search Topic
Unsuccessful Searches
n
%
HIV test
8
38.1
Paxil
4
19.0
Alcoholics Anonymous
3
14.3
tattoo
3
14.3
smoking
2
9.5
diabetes
1
4.8
Total
21
100.0
Certain search actions led to sites that contained the answer more often than others. Overall, students found answers on 22% of the sites they accessed (47 of 215). They accessed sites in 5 ways. Although not often taken, the action with the highest probability of success (47%; 7 of 15) was following a link from 1 non-search-engine site (eg, www.aa-intergroup.org) to another site (eg, www.alcoholics-anonymous.org). In most of these cases, the student accessed the first site directly from a search engine. Clicking on search engine results led to a site where students found an answer 21% of the time (35 of 166). Success rates were similar for following a recommended link from a list or menu provided by the search engine (18%; 4 of 22). Directly typing in a URL, bypassing search engines entirely, was successful only 9% of the time (1 of 11). A sponsored link from a search engine was followed only once, and the student found an incorrect answer on that site.
Another contributing factor related to success was misspelling of search terms. Of the 14 completed but unsuccessful searches, 29% (4 searches) had at least 1 misspelling compared to only 15% (7 searches) of the 47 successful searches. Perhaps even more telling, both successful and unsuccessful searches with misspellings took students 1.5 minutes longer on average than searches without misspellings. Observations confirmed that some students were unable to find an answer until they discovered and corrected their misspelling, resulting in higher quality and more-relevant results.
Other search characteristics did not have statistically significant impacts on whether searches were successful, although this may have been due to small sample sizes. For example, the search engines were not significantly different in their percentages of successful searches. Similarly, the average number of words per search string was not significantly related to search success rate. (Data not shown.)
Qualitative Analysis
Certain common behaviors of the adolescent searchers were observed which were not apparent from the quantitative analysis.
First, the students were very comfortable and confident while searching online for health information. Most students knew where they wanted to start the search and navigated using quick mouse clicks and shortcut keys. However, this characteristic was likely over-represented in our population due to their strong academic performance and Internet proficiency.
Second, several searchers did not take much time in formulating a search strategy or (when applicable) choosing search terms. Instead, these searchers seemed to type in the first search string that came to mind. If the results were not what were anticipated, another search string was typed in, sometimes without even clicking on any results from the first search string. The overall approach was a trial-and-error method with frequent backtracking. The most-common problem with search strings was that they were not specific enough. For example, 2 different students typed in the search string "hiv" when looking for a place that administers free and confidential HIV tests.
Third, most students quickly scanned pages, jumping from place to place within a page, rarely reading an entire paragraph. In some cases the answer to a question was contained on a page, but the student left before finding it. In other cases a link that would have led to the answer was missed. This finding supports prior research on adolescent search behavior related to nonhealth topics [7- 10].
Fourth, students mentioned that they purposefully avoided sponsored links and advertisements, despite the fact that many of the search engines present these results first. The qualitative data confirmed this practice, as only 1 sponsored link was ever selected.
Finally, little to no attention was paid to the source of the answer. In the vast majority of cases, once an answer was located, it was simply assumed to be correct.
Discussion
When compared with prior research, the findings of this study show many similarities and a few key differences between the behaviors of adolescents and adults while searching for health information. This study found that adolescents searching for health information utilized search engines nearly every time. This finding was similar to that for adults as described in the Eysenbach study [15]. These observational studies also suggest that after-the-fact survey questions concerning the use of search engines may underestimate this behavior. For example, 2 nationally-representative surveys reported that 58% of youth (written communication, 2001 Dec; Generation RX.com Survey printouts; V. Rideout, Henry J. Kaiser Foundation, Menlo Park, CA) and 81% of adults [1,2] started seeking health information at search engines. Our study found that adolescents relied upon links from only the first few results pages, and rarely explored far within any site. These results also were similar to adult searching behaviors [15], although youth seem to be more likely to search beyond the first 10 search results. Adolescents often chose search strings that were too general and/or contained misspellings, so that they did not always find useful sites that were available. Eysenbach also reported search strings by adults that were too general [15], however, spelling seems to be more of a problem with youth. Adolescents were unsystematic in their reading of Web sites and some sites were poorly organized so that they did not always find the information they were looking for, even when it was present in a site they examined. Future research is needed to better understand if adolescents do not understand information provided on these sites, whether they simply have less patience, or some other explanation. In summary, many of the specific search tactics are similar for adults and adolescents, but a few issues related to spelling, browsing of Web sites, and understanding of content are notably different.
Simulation of Searches
The results from this study have implications for anyone who simulates adolescent health searches, for providers of health information, and for educators. There are many reasons to simulate adolescent health searches. For example, an educator preparing a lesson plan may want to informally simulate searches in order to anticipate what students are likely to find if given certain particular search tasks. A researcher may want to simulate adolescent searches more systematically to evaluate the availability and accessibility of information on particular topics, to evaluate which search engines should be recommended to adolescents, or to evaluate whether the installation of filtering software will have a detrimental impact on accessibility of health information [13]. Because many of the search behaviors modeled by these simulations are similar for both adolescents and adults, results from studies that simulated one or the other group likely apply to both groups.
The results of this study suggest that such simulations can focus on the use of search engines, but that very-broad search terms and, especially for adolescents, common spelling errors should be considered. Ads and other nonresult links can be ignored. Since more than 80% of the links that were followed appeared in the top 10 results, and more than 95% were among the top 40, a search simulation need not consider result links beyond these.
Providers of Internet Health Content
Given the patterns of adolescent searching behavior found in this study, providers of health content can do several things to increase the probability that adolescents will find their sites. Since adolescents rely primarily on the first few results from search engines and do not tend to look at ads, it is important to ensure that health sites appear near the top of the results for searches on health terms. Choices of keywords in the domain name, page title, meta tags, and the first few sentences, as well as links from other sites, can all affect placement in search results. It may also be useful to include some common misspellings in meta-tag keywords and in the body of the text in order to make a site appear in the results page of searches using those misspellings of related search terms. Because most major English-language search engines no longer use the keyword feature of meta tags, site designers are left with the difficult task of working misspelled words (eg, misspelt) into the text without coming across as poor spellers themselves. It is also important that the site descriptions displayed in search engines be attractive to adolescent searchers: while our study did not analyze the various reasons that adolescents chose to follow one link over another, we did observe that they made choices based upon the link descriptions and did not simply select the first link offered. Books and articles, software, and consulting services are all widely available to improve search engine placement and to influence the short summary text that search engines extract for display in search results [28,29]. Organizations that invest large amounts of money in developing sophisticated health-information sites would do well to spend a little bit more to ensure these sites are easily found.
Another area that Internet content providers should focus on is within-site navigation. Because students tend to skip around from place to place within a page and read little in sequence, it is important that sites with a significant adolescent audience are well organized, concise, and understandable. Long paragraphs, too many links, and difficult vocabulary all decrease the likelihood of adolescents finding health information they are seeking, even if it is contained within a site. Internet content producers should attempt to understand the needs of the site visitors and build hierarchal structures that reflect those needs. For example, if one of the primary needs of individuals visiting the Alcoholics Anonymous site is to find a local meeting, the first page of the site should include an obvious link (eg, "Find an AA Meeting Near You") that leads to another page that returns the nearest meetings after entering in a zip code or city name. While ease of within-site navigation is important for all visitors to health information sites, some information providers may want to develop sites targeted specifically to adolescents. While they might like the targeted information once they found it, we observed that adolescents tend to rely on general-purpose search engines. Thus, developing special youth-targeted versions of information sites may be of somewhat limited utility, unless also accompanied by advertising or education campaigns that make adolescents more likely to find such sites.
Rather than changing Web sites or their presentation in search engines, it may also be useful to undertake education campaigns to improve the search strategies and tactics that adolescents use when seeking health information. It may be helpful to guide them towards youth-oriented directories or search engines, rather than general-purpose search engines. For example, both Yahoo! and Google offer directories with subcategories of sites designed for teens that cover various health topics. This approach may be facilitated by including links to such resources on the Web browser's starting page in schools and libraries. Alternatively, adolescents might be taught techniques for formulating and refining search terms at general-purpose search engines, adding or dropping more-specific words based on the kinds of results returned. They might also be taught to notice potential search term misspellings based on surprising search results. Finally, adolescents might also be taught techniques for systematically exploring within a Web site to find the kind of information they are looking for.
Limitations and Future Research
There are several important limitations to the interpretation of these results.
First, this was not a representative or random sample of adolescents. It was a small convenience sample with a selection bias toward adolescents with strong Internet searching skills. While the results cannot be generalized to all adolescents and do not capture the full range of adolescent searching experience, we can assume that the average adolescent would have had even more trouble than our study participants in finding health information on the Internet.
Second, the health-related search questions were deliberately constructed to avoid controversial topics such as safe sex, abortion, and homosexuality. Given that adolescents are often faced with health problems related to sexuality, their actual search behavior and success at finding health information related to sexuality may not be reflected in our results. Another concern is that participants may have changed their search behavior because of the presence of observers and because they were aware that their search behaviors were being recorded. For example, students who had trouble finding an answer may have persisted in their search longer than they would have in a nonresearch setting. Alternatively, because students knew they had several search questions to answer during a single class period, they may not have been as persistent as they might have been with a more personally-relevant question and less-restricted search time. Thus, the data here reflect a rough estimate of persistence for an adolescent looking for health-related information. Also, searching was conducted individually, while in practice many searches both at home and at school are conducted with friends, teachers, or family close by. While it is difficult to know how this would affect searching behavior without future research, it is possible that students would act differently (eg, receive help with spelling).
Finally, while components of our classification scheme for successful versus unsuccessful searching have been previously validated, the overall scheme was modified to more accurately code the search results as correct, complete, and useful. A more-systematic validation of coding schemes for health information search results is an important area for future research.
More research is needed to validate the results presented in this article, as well as determine if results vary for different populations (eg, age, race, and experience with health searching) and different health questions (eg, finding a practitioner versus finding the answer to a question). Additionally, instead of focusing on how adolescents currently search for health information, future studies may also want to explore interventions aimed at improving their searches. For example, should health portal sites designed for adolescents or online directories be used? Or would the current practice of using common search engines, but with adolescents learning improved search tactics be more effective? Also, which search strategies lead to sites that are the most likely to be accurate and influence adolescents to change their behavior?
Conclusions
This study provides a useful snapshot of current adolescent searching patterns. The results have implications for constructing realistic simulations of search behavior, and for both information providers and educators. Analyzing search behavior through actual observation should be a cornerstone in any effort to improve adolescents' access to health information.

adolescent
internet
computer literacy
access to information
medical informatics
health education
computer simulation
search process
information seeking
information storage and retrieval


Subintimal Double-Barrel Restenting of an Occluded Primary Stented Superficial Femoral Artery

In-stent re-stenosis is a frequent complication of endovascular stents, especially in the superficial femoral artery (SFA). Endovascular re-intervention of in- or peri-stent occlusive disease consists of recanilization through the occluded stent. In our case report, we describe the endovascular treatment of a previously placed stent in the SFA. We unintentionally passed the affected stent subintimally, in a double barrel fashion next to the first stent. The procedure was without any complications and with a successfull angiographic result. At one year follow-up the patient still has no complaints and the stent is still patent.
In-stent restenosis is a frequent complication, especially in the superficial femoral artery (SFA). If in-stent restenosis occurs there are several therapeutic options available such as conservative therapy and endovascular or surgical intervention. Endovascular reintervention of in- or peri-stent occlusive disease is one of the less invasive options. Endovascular therapy means passage through the occluded stent (recanalization) by additional means and redilatation or restenting of the lesion. In some cases passage of the occluded stent is not possible.
In this case report we describe the unsuccessful attempt to recanalize an occlusion in a stent in the SFA followed by the successful bypass of the stent using a subintimal technique. The concept of utilizing this secondary stent was to create enough radial force to keep open the neo-lumen next to the occluded stent. Although the per-interventional extraluminal recanalization (PIER) technique is usually performed for longer lesions of the SFA, in this case a shorter segment was successfully managed [1, 2].
An internet search for articles describing equivalent cases revealed no results. No publications on subintimal passage of a reoccluded stent and double-barrel stenting were found in the literature.
Case Report
A 75-year-old man underwent several percutaneous transluminal angioplasty (PTA) procedures in both upper leg vessels as well as stenting of a right SFA lesion in the adductor canal after an insufficient PTA result in an other facility (Figs. 1 and 2).
Fig. 1.
See text.
Fig. 2.
See text.
The patient presented in 2004 with progressive complaints of the right leg. The patient’s maximum walking distance was 800 m but he smoked 5–10 cigarettes a day. As consistent medication the patient was on antihypertensive drugs, 40 mg simvastatin (10 mg Zocor, MSD) as well as 100 mg carbasalaatcalcium (Ascal Cardio, Viatris). There was no cardiopulmonary comorbidity.
Right pedal pulses were absent with a normal pulse at the right groin. Blood pressure was 160/95 mmHg. The maximum walking distance was 160 m with a drop in the ankle/brachial index (ABI) after excercise of 0.62 to 0.23 on the right side and 0.98 to 0.55 on the left side. In conclusion, this patient had peripheral arterial occlusive disease (PaOD) staged as Fontaine class 2a.
A color Doppler ultrasound (CCDS) examination of the right femoropopliteal arteries revealed in- and peri-stent restenosis with a peak systolic volume (PSV) ratio of 5.7 and distal in-stent occlusion noted over 4 cm. At that time the patient could not be persuaded to undergo any intervention and was managed conservatively.
In March 2005 the patient presented again with unchanged symptoms. On physical examination the walking distance was now 240 m with an ABI drop after excercise of 0.44 to 0.22 on the right side and 0.91 to 0.52 on the left side. The patient and his attending physician discussed endovascular treatment such as recanalization of the affected vessel with PTA and/or additional stenting as a proper next option for his PaOD Fontaine class 2a lifestyle-limiting symptoms.
In April 2005, an endovascular percutaneous intervention of the right SFA was performed at the Department of Radiology in our hospital. Because the patient was overweight an antegrade puncture was not a good option and the right SFA was approached by a crossover technique from the contralateral side. The right leg vessels were visualized angiographically demonstrating a stenosis of approximately 70% at the origin on the right SFA. More distally in the SFA an occlusion was noticed reaching from 4 cm proximal of the occluded stent to the upper border of the patella (The total length of this lesion was approximately 11 cm.) The 5 Fr Brite Tip sheath (Cordis, New York, USA) in the right femoral artery was changed for a long 6 Fr Balkin Up & Over flexorsheath (Cook, Bloomington, IN, USA). The sheath tip was placed in the left external iliac artery, just above the hip joint. First a PTA was performed at the origin of the SFA with a 6.0/40.0 mm balloon (Pheron, Biotronik, Switzerland) after an intravenous (IV) injection of 2,500 IU heparin, with a satisfactory angiographic result. However, it proved impossible, after several catheter-guidewire manipulation efforts, to recanalize the occluded stent with a 0.035-inch J-shaped Terumo (Terumo, USA) guidewire. Next the occluded stent was bypassed subintimally PIER-wise and the native lumen successfully re-entered just distal to the occlusion. The neo-lumen thus created was predilated with an unsatisfactory result due to recoil and consequently stented with a self-expandable 6.0/60.0 mm and a 6.0/80.0 mm stent (Absolute, Guidant, Indianapolis, IN, USA). Post-dilatation was performed with a 6.0 mm Pheron balloon. Angiographic verification of the treated arterial segment revealed an acceptable angiographic result and good runoff to patent vessels below the knee. The 2,500 IU heparin was antagonized by an IV injection of 2,500 IU protamine. The angiographic sheath was withdrawn and the puncture site managed by manual compression for 10 min without any problems. The procedure was carried out without any minor or major events or complications.
One day after the procedure the patient underwent CCDS proving patency of the treated proximal SFA and newly inserted stents with no residual stenotic segments. The ABI on the right side was 1.0 and on the left side was 1.1. The patient reported a slightly painful sensation on the upper-medial side of his lower (treated) limb.
On his planned check-up at the department of surgery in May 2005 the patient reported himself very satisfied with the result. The pain sensations had disappeared and there were no more limitations to his walking distance.In August 2005 his ABI on the right side was 0.85 with a drop, after exercise, to 0.25. On the left side his ABI was 0.88 with a drop, after exercise, to 0.62. On color Doppler ultrasound investigation a patent secondary stent segment and no new stenotic lesions were observed and a normal flow pattern was described.
Discussion
Peri- and in-stent restenosis is a common and well-known complication in the SFA region. There are several therapeutic options to solve this problem including endovascular treatment and bypass surgery. Because of our patient’s physical condition and his lifestyle-hampering symptomatology we chose was endovascular treatment in an attempt to recanalize the affected stent.
During the procedure it proved impossible after several attempts to recanalize the occluded stent in the SFA, probably because of already organized and fibrosed thrombus material in the stent. The crossover was not the cause of this failure, since the pushability and steerability of the guidewire-catheter assembly was sufficient. No angioplasty could be performed in the occluded stent. After several attempts we finally managed to pass the occluded stent subintimally, successfully re-entering the native lumen distally and creating a neo-lumen side-by-side with the primary occluded stent. The neo-lumen was stented to create enough radial force to prevent its elastic recoil. Two self-expandable stents were positioned in a double-barrel fashion alongside the previously occluded stent with proper clinical and angiographic result.
A retrograde puncture was preferred because of the lower complication rate compared with an antegrade approach in this obese male. Moreover a crossover introducer sheath assembly creates more possibilities for easier catheter-guidewire manipulations.
Conclusion
If a patient presents with claudication symptoms caused by in-stent restenosis or occlusion, one can try to recanalize the occluded stent. This is often not possible, especially if the occlusion is of an older date and consists of fibrosed tissue, mainly because of reorganizing thrombus. Mechanical debridement is an option, but this is more successful in (sub)acute (re)stenosis [3]. Subintimal passage of a occluded stent using the PIER technique could be an option in such cases. The PIER technique is intended as a primary therapy, usually for longer lesions of the SFA and for patients with severe (critical) limb ischemia, and has a 1-year patency rate of 22% and a success rate of 62% [1, 2]. As shown in our case, PIER appears to be good not only for recanalizing occlusions but also for providing options for the treatment of nonpenetrable in-stent occlusions by trespassing PIER-wise and subintimal stenting of the neo-lumen.

superficial femoral artery
endovascular stenting
pier
interventional radiology
reocclusion


Clinical impact of HLA class I expression in rectal cancer

Purpose To determine the clinical impact of human leukocyte antigen (HLA) class I expression in irradiated and non-irradiated rectal carcinomas.
Introduction
The immune system is thought to have an important function in controlling tumor growth and eliminating metastasizing tumor cells. The expression of human leukocyte antigen (HLA) class I, presenting tumor-associated antigens on the tumor cell surface, is considered as a prerequisite for an effective T cell immune response [34]. As a consequence, tumor cells with down-regulated HLA class I expression might escape this immune response, resulting in a selective outgrowth of these tumor cells.
Many studies described HLA class I expression in cancer [10, 17, 22, 33]. Only limited studies have reported on the clinical impact of HLA class I expression in colorectal cancer with contrasting results. Some studies found no significant correlation between staining intensity and survival [1, 19, 20], while others found a prognostic correlation between HLA expression and survival [18, 35]. The latter two studies had in common that total absence of HLA class I resulted in a favorable prognosis as compared to patients with down-regulated expression of HLA class I of tumor cells. The discrepancy between these two studies is, whereas the one described high expression of HLA class I in tumor cells that resulted in a better prognosis as compared to the partial down-regulation of HLA class I [35], the other found the opposite [18]. These studies both analyzed a mixed population of colon and rectal cancer patients. For rectal cancer patients, the clinical impact of HLA class I expression is still unknown. Since HLA class I expression is often absent in microsatellite instable (MSI) tumors [9, 16] and MSI is more frequently observed in right-sided colon tumors than in rectal tumors [30], therefore the results obtained from a mixed population of colon and rectal cancer patients might not hold true for rectal cancer patients.
The purpose of this study was to analyze the clinical relevance of HLA class I expression for rectal cancer patients. In addition to determining the impact of MSI on HLA class I expression, the tumors most at risk for MSI i.e. HLA-negative tumors were examined for MSI by determining the expression of the mismatch repair proteins, mismatch mutL homolog 1 (MLH1) and postmeiotic segregation increased 2 (PMS2), that are most absent in sporadic MSI tumors [7, 36]. Radiotherapy has been described recently to increase cell surface expression of major histocompatibility complex (MHC) class I molecules in a murine colon adenocarcinoma cell line [26]. Therefore, our study also evaluated the effect of radiotherapy on HLA class I expression in rectal cancer patients. For these purposes, HLA class I expression was evaluated in a set of 1,135 formalin-fixed paraffin-embedded rectal cancer specimens. The tumors studied were obtained at the time of surgery from patients of a prospective multicenter trial, who were randomized between standardized preoperative radiotherapy treatment followed by surgery or surgery alone [15].
Materials and methods
Study population
Patients were obtained from the Dutch TME trial, a multicenter trial that evaluated total mesorectal excision (TME) surgery with or without preoperative radiotherapy (5 × 5 Gray) [15]. Radiotherapeutical, surgical and pathological procedures were standardized and quality-controlled [15, 21]. Tumor staging was determined using the tumor node metastasis (TNM) classification [29]. Patients with the hereditary Lynch syndrome also known as hereditary non-polyposis colorectal cancer (HNPCC) were excluded from the TME trial. Sufficient formalin-fixed paraffin-embedded tumor material was available for 1,135 Dutch patients. Three 2 mm cores of each tumor sample were arrayed into tissue microarrays (TMA) as previously described [5].
Immunohistochemistry and microscopic analysis
TMAs [5] were immunohistochemically stained for HLA class I using the mAb antibodies HCA2 and HC10 and the rabbit anti-β2 m polyclonal Ab (A 072; DAKO Cytomation, Glostrup, Denmark). The HCA2 and HC10 antibodies were applied in immunohistochemistry as hybridoma culture supernatant, kindly provided by Prof. J.J. Neefjes from the Netherlands Cancer Institute (Amsterdam, The Netherlands). The reactivity spectrum of HCA2 includes HLA-A (except HLA-A24), HLA-B73 and HLA-C molecules as well as HLA-E, HLA-F and HLA-G antigens [27, 28, 31]. HC10 reacts with HLA-B and HLA-C molecules and HLA-A10, -A28, -A29, -A30, -A31, -A32 and -A33 heavy chains [13, 23, 31, 32]. The immunohistochemical procedures are described in detail elsewhere [18]. All tumor specimens were stained simultaneously to avoid intra-assay variation. Microscopic analysis was assessed by two independent observers (M.M. v. B. and M. v. V.) in a blinded manner. HCA2, HC10 and β2 m stainings were scored in six categories. Essentially, the scoring was divided into quartiles but for tumors with less than 25% stained cells, there was a distinction made between those with 6–25% positively stained tumor cells, those with approximately 1–5% positively stained cells and those with absolute no positively stained tumor cells [3, 11]. Where discrepancies arose between the staining of cores from the same tumor, an average of the scores was taken, with confirmation by two observers using a double-headed microscope with a consensus decision taken in all cases. Tissue stromal cells, normal epithelium or lymph follicles served as positive internal controls to ascertain the quality of the staining. Patients were excluded if stromal cells of tumor were not stained for HCA2 or HC10. Twenty-five tumors with negative staining of the stromal cells for HCA2 were excluded. HC10 showed in all tumors staining of the stromal cells. Also TNM stage 0 patients, tumors lost due to technical failure and ineligible patients were excluded, leaving 1,092 tumors in which HC10, and 1,035 in which HCA2 could be evaluated. Combining the results for HCA2 and HC10 staining resulted in 1,008 eligible stage I–IV rectal cancer patients for analyses of clinical impact of HLA class I expression.
Tumors negatively stained for HCA2 and/or HC10 were stained for mismatch repair proteins MLH1 and PMS2. MLH1 and PMS2 are deficient in sporadic MSI tumors. Therefore, the expression of these proteins was used to differentiate MSI and MSS rectal cancers. Tissue stromal cells, normal epithelium or lymph follicles served as positive internal controls when analyzing MLH1, PMS2 expression. The expression of MLH1 and PMS2 was scored positive if tumor cells showed expression, and negative if tumor cells showed no expression of either MLH1 or PMS2, provided that and tissue stromal cells did show expression, indicating microsatellite stable (MSS) and microsatellite instable (MSI) tumors, respectively [7].
Statistical analyses
All analyses were performed with SPSS statistical software (version 12.0 for Windows, SPSS Inc, Chicago, USA). Mann–Whitney U, t test and χ2-tests were used to compare variables. Kaplan–Meier analyses were performed to analyze patient survival. The entry date for the survival analyses was the time of surgery of the primary tumor. Events for time to local recurrence, distant recurrence, cancer-specific survival, disease-free and overall survival were defined as follows: from time of surgery to time of local disease relapse (for local recurrence), time of distant disease relapse (for distant recurrence), time of disease relapse or death by disease (for cancer specific survival), time of disease relapse or death (for disease free survival) and time of death, respectively (for overall survival). Non-irradiated and irradiated patients were first separately analyzed in univariate analysis and second, variables with a P value of <0.10 in the univariate analyses were subjected to a multivariate analysis. Multivariate analysis was performed on the whole group of irradiated and non-irradiated patients with the following variables: HLA class I, randomization for radiotherapy, TNM and circumferential margin. Cox’ regression analyses were used to calculate hazard ratios (HR) with 95% confidence intervals (CI).
Results
Scoring methods
Several methods are described to analyze HLA class I expression in cancer. The standard is defined by the International HLA and Immunogenetics Workshop (IHIW) [3, 11]. A recent paper describing HLA class I expression in colorectal cancer used an adjusted form of this scoring method [35]. Our scoring was primarily adapted from IWIH, i.e. division into quartiles, but for tumors with less than 25% stained cells a distinction was made between those with 6–25% positive tumor cells, those with approximately 1–5% positive tumor cells and those with absolute no HLA class I positive-stained tumor cells. After scoring and analyzing this method we found that patients in the groups with absolute numbers, 1–5%, 6–25% and 26–50% HLA class I expression of tumor cells did not differ in prognosis but had a worse prognosis as compared to patients with HLA class I expression in groups with 50–75% and >75% of tumor cells expressing HLA class I. Therefore, we distinguished two categories. These two categories were (1) 0–50%; and (2) >50–100% of tumor cells expressing HLA class I.
HCA-2 and HC10 staining in rectal cancer
Immunohistochemical staining with HCA2 and HC10 antibodies demonstrated strong positive membrane staining of stromal cells and tumor-infiltrating inflammatory cells, indicating the success of the staining. A total of 1,035 and 1,092 tumors were evaluated with HCA2 and HC10; 324 (65%) irradiated tumors and 312 (58%) non-irradiated tumors showed at least 50% of all tumor cells positive for HCA2. Staining with HC10 resulted in 403 (76%) irradiated tumors and 436 (77%) non-irradiated tumors that showed more than 50% positive tumor cells. The complete results are shown in Table 1. Representative examples of the immunohistochemical stainings of tumors are displayed in Fig. 1a–f. These results show that about 35% of irradiated and 42% of non-irradiated patients showed less than 50% of the tumor cells expressing HCA2. HC10 is expressed in less than 50% of the tumor cells in about 25% of both irradiated and non-irradiated rectal cancer patients.
Table 1Most rectal tumors have high numbers of tumor cells positive for HCA2 or HC10Irradiated patients N (%)Non-irradiated patients N (%)HCA2 High324 (65%)312 (58%) Low142 (28%)174 (32%) Absence31 (6.2%)52 (9.7%)HC10 High403 (76%)436 (77%) Low117 (22%)116 (21%) Absence8 (1.5%)12 (2.1%)Numbers (N) of patients are indicated with percentages shown in parentheses, showing: expression of HCA2 and HC10 in more than 50% of the tumor cells (high), expression in less than 50% of the tumor cells (low) and total absence (absence)Fig. 1Examples of HCA2 and HC10 immunohistochemical staining of rectal tumors; a–c HCA2, d–f HC10 expression. a, d Expression of HLA class I in >50% tumor cells; b, e expression of HLA class I in <50% tumor cells; c, f epithelial cells show total absence for HCA2 or HC10 and only stromal and infiltrative cells show positive staining for HCA2 or HC10; Original magnification ×20
Analysis of HLA class I expression in rectal tumors
Together, the results obtained with HCA2 and HC10 are expected to reflect HLA class I expression in rectal cancer. In a group of 64 tumors it was studied whether an additional staining for β2 m would better define HLA class I expression. The results of the addition of β2 m to HCA2 and HC10 were comparable to those obtained with HCA2 and HC10, i.e. only 1 of 64 tumors was differently classified. Therefore, β2 m was not scored in the whole cohort and HLA class I expression was assessed by combining HCA2 and HC10.
A total of 406 (85%) irradiated and 445 (84%) non-irradiated tumors exhibited expression of at least one of the two markers showing >50% positive staining of all tumor cells (further referred to as ‘the HLA class I high expression group’). A total of 70 (15%) irradiated and 87 (16%) non-irradiated tumors showed reduced numbers (≤50%) of HLA class I positive tumor cells. Only 3 (0.6%) irradiated tumors and 8 (1.5%) non-irradiated tumors showed total loss of HLA class I (negative for both HCA2 and HC10). Survival results of patients with total absence of HLA class I on tumor cells did not show significant difference from patients with reduced numbers of HLA class I positive tumor cells. Therefore, these groups were combined and will be further referred to as ‘the HLA class I low-expression group’. The complete results are shown in Table 2. The number of patients in the group of the HLA class I high-expression group and the HLA class I low-expression group was equally distributed between irradiated and non-irradiated tumors (χ2 = 0.519, P = 0.471), indicating that irradiation had no effect on HLA class I expression in these patients.
Table 2Expression of HLA class I in rectal cancer using HCA2 and HC10 antibodiesHCA2HC10HLA class IHigh (N)Low + absence (N)N (%)IrradiatedHigh (N)27037406 (85%)Low + absence (N)997070 (15%)Non-irradiatedHigh (N)27732445 (84%)Low + absence (N)1368787 (16%)Expression of results of HCA2 and HC10 staining in a cross table for numbers (N) of irradiated and non-irradiated patients; expression of HCA2 and HC10 in more than 50% of the tumor cells (high) versus expression in less than 50% of the tumor cells (low) is shown. A significant correlation was noted between HCA2 and HC10 staining for both irradiated (χ2 = 53.947, P < 0.001) and non-irradiated patients (χ2 = 61.257, P < 0.001). The right side of the table displays HLA class I expression estimated on HCA2 and HC10 expression. A total of 406 (85%) irradiated and 445 (84%) non-irradiated tumors exhibited expression of at least one of the two markers showing >50% positive staining of all tumor cells. A total of 70 (15%) irradiated and 88 (16%) non-irradiated tumors showed reduced numbers (≤50%) of HLA class I positive tumor cells. The number of patients in the group of the HLA class I high expression group and the HLA class I low expression group was equally distributed between irradiated and non-irradiated tumors (χ2 = 0.519, P = 0.471)
HLA class I negative cells and microsatellite instability
It has been described that a majority of MSI colorectal tumors do not express HLA class I, while only a minority of MSS tumors do not express HLA class I [8, 16]. Therefore, HLA class I negative rectal tumors are the most at risk to be MSI tumors. To evaluate the numbers of sporadic MSI tumors in our study, HCA2 or HC10 negative tumors were analyzed for the expression of PMS2 and MLH1. PMS2 and MLH1 are mismatch repairs proteins that are most frequently absent in MSI sporadic tumors [6]. Of the HLA class I negative tumors only 1 out of 11 tumors did not express PMS2 and MLH1. In the tumor group negative for only 1 of the 2 HLA class I markers, 2 of 81 tumors displayed no PMS2 and MLH1 staining. These results indicate that HLA class I down-regulation is not associated with MSI in rectal cancer and are in accordance with the previous findings that only a very small minority of rectal tumors are MSI [4, 25].
HLA class I expression and clinicopathological parameters
The relationship between HLA class I expression and patient/tumor characteristics was assessed (Table 3). The HLA class I expression levels were distributed equally in non-irradiated and irradiated patients with regard to most clinical and pathological parameters. Three significant differences were observed. For the non-irradiated patients, significantly more men appeared in the HLA class I low-expression group (P = 0.03). The group of irradiated tumors with HLA class I low expression contained significantly more stage III and IV tumors (P = 0.01) and also more patients with a tumor-positive circumferential resection margin (P = 0.02) when compared with tumors with high HLA class I expression.
Table 3Clinicopathological characteristics of irradiated and non-irradiated patients with high or low numbers of HLA class I positive tumor cells Non-irradiated patientsIrradiated patientsHigh N = 445Low N = 87P valueHigh N = 406Low N = 70P valueGender Male (%)63750.0365660.90Age Median years65680.3265650.99TNM stage (%) I31240.5233240.01 II27303021 III36383240 IV58514Circumferential margin Negative (%)83770.2886740.02Distant from anal verge (%) ≥10 cm28330.1727320.30 5–10 cm41314636 < 5 cm31362732Operation type (%) Low anterior resection66610.7765660.89 Abdomino-perineal resection29332930 Hartmann5664Number (N) of patients with expression of total HLA class I expression in more than 50% of the tumor cells (high) and expression in less than 50% of the tumor cells (low)* Statistical significant P values are in bold
Expression of HLA class I and clinical prognosis
Because radiotherapy might influence local tumor recurrences [15], irradiated and non-irradiated tumors were analyzed separately in order to evaluate the impact of HLA class I expression on tumor recurrence and patient survival. The HLA class I expression was not related with distant or local recurrence rates. The patients with low expression of HLA class I had a worse overall survival and disease-free survival when compared to patients with HLA class I high expression, irrespective of treatment (Fig. 2; overall survival: P = 0.008 and P = 0.01; disease free survival: P = 0.01, P = 0.006 in irradiated and non-irradiated patients, respectively). Irradiated patients with low HLA class I expression also had a worse cancer-specific survival (P = 0.003). For non-irradiated patients, HLA class I expression had no significant effect on cancer-specific survival (Fig. 2). All results of univariate analysis are shown in Table 4. Univariate analysis showed a better outcome for overall survival and disease-free survival in patients with high HLA class I expression.
Fig. 2Examples of Kaplan–Meier curves showing overall survival and cancer specific survival for irradiated and non-irradiated patients (a–d). Kaplan–Meier curves for overall survival (a, b) and cancer specific survival (c, d); curves show prognosis for non-irradiated (a, c) and irradiated patients (b, d) for HLA class I expression in more than 50% of the tumor cells (high) versus expression in less than 50% of the tumor cells (low). P value is based on univariate log rank analysesTable 4Both irradiated and non-irradiated patients with high expression of HLA class I have a better overall, and disease free survivalNon-irradiated patientsIrradiated patientsHigh (%)Low (%)P valueHigh (%)Low (%)P valueOverall survival65.558.50.01267.551.30.008Disease free survival62.253.50.01562.248.30.006Cancer specific survival74.371.40.4180.161.80.003Local recurrence8.913.70.224.73.20.72Distant recurrence26.728.70.8824.729.30.34Survival and recurrence rates indicated in percentages after 5-years of follow-up for non-irradiated and irradiated patients for HLA class I expression in more than 50% of the tumor cells (high) versus expression in less than 50% of the tumor cells (low). P value is based on univariate log rank analyses for overall survival, disease free survival, cancer specific survival, local recurrence and distant recurrence* Statistical significant P values are in bold
Multivariate analysis
Multivariate analysis was performed to identify factors with independent prognostic significance and to calculate hazard ratios (HR). Analyses included TNM, circumferential margin, randomization for preoperative radiotherapy and HLA class I expression (low vs. high HLA class I positive tumor cells) (Table 5). Advanced pathological (TNM) stage and tumor-positive circumferential resection margins retained their strength as independent prognostic factors in these survival analyses. HLA class I expression showed independent prognostic value for overall survival and disease-free survival (HR: 1.3, P = 0.042 and HR: 1.4, P = 0.006, respectively), but not for cancer-specific survival.
Table 5Multivariate analysis confirms independent better overall, and disease free survival for rectal cancer patients with high expression of HLA class IOverall survivalDisease free survivalCancer specific survivalHR (95% CI) P valueHR (95% CI) P valueHR (95% CI) P valueHLA High10.04210.00610.653 Low1.3 (1.0–1.6)1.4 (1.1–1.8)1.1 (0.8–1.5)Randomization TME10.63210.21410.282 TME + RT1 (0.8–1.2)0.9 (0.7–1.1)1.1 (0.9–1.5)TNM I111 II2.2 (1.7–3.0)<0.0012.1 (1.6–2.8)<0.0013.5 (2.0–6.1)<0.001 III3.1 (2.4–4.1)<0.0013.1 (2.3–4.0)<0.0019.0 (5.4–14.9)<0.001 IV11.8 (8.1–17.1)<0.001––50.3 (28.5–89.1)<0.001CRM Negative1<0.0011<0.0011<0.001 Positive1.3 (1.1–1.5)1.8 (1.4–2.2)1.3 (1.1–1.5)Multivariate analysis for cancer specific, overall and disease free survival was performed to identify factors with independent prognostic significance and to calculate hazard ratios (HR) with 95% confidence intervals (CI) shown in parentheses. HLA class I expression in more than 50% of the tumor cells (high) versus expression in less than 50% of the tumor cells (low), total mesorectal excision (TME), Radiotherapy (RT); circumferential margin (CRM); P value is based on Cox’ regression analyses* Statistical significant P values and HR are in bold
Discussion
We showed that rectal cancer patients from the HLA class I low expression group had an independent worse overall and disease-free survival when compared to patients from the HLA class I high-expression group. These data imply that the expression of HLA class I in tumor cells predicts survival for rectal cancer patients. Although significant better cancer-specific survival for irradiated patients with high HLA class I was found in univariate analysis, the predictive value was lost in multivariate analysis. This observation can be explained by the fact that the group with low HLA class I significantly included more stage III/IV and more patients with a positive circumferential margin as compared to the group of patients with high expression of HLA class I. Also no predictive value of HLA class I expression was found with regard to recurrence-free survival of these patients. Therefore, we have no indications that support the notion that better survival of high HLA class I expression is due to the better antigen presenting function of these tumor cells, as has been suggested [18, 35].
In our study, no difference was found between irradiated and non-irradiated patients for HLA class I expression in tumor cells. It has been described that γ-irradiation induces enhanced peptide production and surface expression of MHC class I in a colorectal mouse tumor cell line [26]. The fact that we could not find more HLA class I expression in irradiated tumors than in non-irradiated tumors indicates that radiotherapy does not induce HLA class I expression in vivo. Immunohistochemistry, however, is less suitable to measure subtle expression changes. Therefore, additional research is required to determine the impact of radiotherapy on expression levels of HLA class I in human tumors.
In our study, more tumors showed HLA class I down-regulation after immunohistochemical staining using HCA2 than using HC10. This difference might be due to differences in reactivity spectrum of both antibodies (see Materials and methods) or to the fact that HLA alleles are differently affected in colorectal cancer. If the latter is the case, our results suggest that HLA A alleles preferentially show down-regulation in rectal cancer.
Previous reports evaluated HLA class I expression in mixed patient populations of colon and rectal cancer patients [18, 35]. Watson et al. also found in a large group of colorectal cancer patients that patients with low expression of HLA class I had a poor prognosis [35]. However, in contrast to our results, both studies described a substantial population of patients with tumors showing absence of HLA class I. In addition, they described that absence of HLA class I was associated with better prognosis as compared to tumors expressing reduced numbers of HLA class I positive tumor cells. A relatively low number (1.1%) of HLA class I negative tumors was observed in our cohort of rectal cancer patients only. These patients showed no survival advantage when compared to patients with reduced numbers of HLA class I positive tumor cells. There are several explanations for the discrepancy in the number of HLA class I negative tumors between the study of Watson et al. and ours, like different definition of HLA class I expression, differences in staining techniques, different patient cohort and number of MSI tumors.
We showed that tumors that do not stain HC10 can stain positive for HCA2 and thus are still able to present antigens. Therefore, an explanation for the differences with the results of Watson et al. is that we used strict criteria to classify tumors as HLA class I absent (defined as both HCA2 and HC10 negative) as compared to Watson et al. (defined as negative for HC10 or negative for β2 m instead of negative for both). Another important explanation is that we examined HLA class I expression in a relative more homogeneous population of patients with a rectal tumor, while the other cohorts are more heterogeneous, consisting of both colon and rectal cancer. Although combining results from colon and rectum is generally accepted when predicting prognosis, this might influence results [14].
In colon cancer patients, approximately 50% of all proximal colon tumors show MSI, whereas almost all distal colon and rectal cancers are MSS tumors [24, 30]. Loss of HLA class I has been described in at least 60% of all sporadic right-sided MSI colorectal tumors but in only 17% of MSS right-sided colon tumors loss of HLA class I is found [8, 16]. In our cohort, only 1 out of 11 HLA negative tumors and 2 out of 81 tumors negative for HCA2 or HC10 did not express MLH1 and PMS2 and were thus likely MSI tumors. This indicates that rectal cancers are mainly MSS tumors, as has previously been described [4, 14, 25]. Of the multiple mechanisms that have been shown to underlie defects in HLA class I expression in colorectal cancer (mutations in the individual HLA class I genes, mutations in β2 m [16], and defects in components of the HLA class I-associated antigen processing machinery (APM) [2, 16]), only the first will result in allele-specific aberrancies while the other affect total HLA class I expression and may result in total absence in a tumor cell.
These observations imply that a population of colorectal tumors with total absence of HLA class I probably contains a disproportionate large number of MSI tumors when compared to colorectal tumors expressing HLA class I. In addition, MSI colorectal tumors have a better prognosis when compared to MSS colorectal tumors [12, 24]. Therefore, HLA class I negative tumors are more likely to be MSI tumors with a different clinical behavior as compared to MSS colorectal tumors. It is likely that MSI influences prognostic results when considering HLA class I expression in colorectal tumors.
Our results show that HLA class I expression in rectal cancer affects the patient’s prognosis. We hypothesize that both oncogenic pathway and HLA class I expression dictate clinical tumor progression. We suggest that in future prognostic studies, analyzing expression of HLA class I or other biomarkers in colorectal cancer, the impact of MSI should be considered.

hla class i
rectal cancer
prognosis
immunohistochemistry
immunology