JRSM >
Volume 96, Number 9 >
Pp. 442-448
1 Institute of Theoretical Surgery, Philipps-University Marburg, Germany
2 Association of the Scientific Medical Societies, Germany
3 Department of Visceral, Thoracic and Vascular Surgery, Philipps-University
Marburg, Germany
Correspondence to: Ina Kopp MD, Institute of Theoretical Surgery, Philipps-University Marburg, 35033 Marburg/Germany E-mail: kopp{at}mailer.uni-marburg.de
 | SUMMARY |
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 TOP SUMMARY INTRODUCTIONMETHODSRESULTSDISCUSSIONREFERENCES |
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Non-participants and poor compliers were older, were more likely to receive palliative (rather than curative) treatment, and had worse scores for physical status. Tumour progression and therapeutic interventions were more frequent in poor compliers than in good-compliers. Patients with risk factors (age 475 years, poor physical status, palliative treatment) were more likely to have missing questionnaires and critical QoL scores in respect of physical functioning and global quality of life over the course of 2 years.
Missing values for QoL have clinical as well as methodological implications, because QoL scores can enhance a clinician's insight. Unwillingness to fill in a questionnaire is an indicator of serious illness. Studies that report sample statistics without specifying compliance rates and the characteristics of non-compliers will give a misleadingly positive picture.
| INTRODUCTION |
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TOPSUMMARYINTRODUCTIONMETHODSRESULTSDISCUSSIONREFERENCES |
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Numerous papers have addressed QoL in rectal cancer,12–16 but the results are not consistent. For example, some groups report QoL to be better after sphincter-preserving surgery (no stoma) than after abdominoperineal extirpation with stoma, but others find no advantage.12,16–18 Part of the explanation for such discrepancies may lie in missing data, and statisticians have proposed various ways to adjust for the deficits.19–22 However, such approaches will not greatly aid understanding of QoL results until we know how the non-availability of data relates to the clinical and psychological state of the patient. There is already reason to think that healthier patients are more likely to answer the questionnaires.23–25 Either severely ill patients may feel too unwell to participate or the researchers may judge them too unwell. Whatever the reason, use of the available data will tend to overestimate quality of life and bias comparisons between treatment effects.26,27 We therefore explored this issue in a cohort of patients with rectal cancer. The hypothesis to be tested was that compliance with QoL testing is associated with physical status. We also examined the relation between compliance and the recording of critical values (very poor scores).
| METHODS |
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TOPSUMMARYINTRODUCTIONMETHODSRESULTSDISCUSSIONREFERENCES |
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Endpoints of the study were self-reported quality of life and quality indicators for primary (operative and adjuvant) treatment for rectal cancer derived from clinical practice guidelines.31–33 Secondary endpoints were compliance rates for QoL assessment and clinically relevant events in the course of the disease during the follow-up period. These were defined as events that contributed to mortality or had therapeutic consequences (change/discontinuation of adjuvant therapy, readmission to hospital, or surgical intervention).34
The study was explicitly observational—i.e. patients were free to take part in the routine follow-up programme or not, and to choose the hospital or the medical practitioner offering this service. To optimize comprehensive data acquisition, an organizational system based on a quality circle and a managing study team was established. The quality circle consisted of surgeons of each hospital, representatives of all occupational groups caring for rectal cancer patients and representatives of the patient self-help groups. The circle functioned as a forum to facilitate clinical adoption of the QoL concept, to discuss local options of rectal cancer care, and to monitor performance of the study. The managing study team consisted of a surgical trainee, a psychologist and a data manager. The team was responsible for providing information on and advice to participating physicians and patients, logistic support (questionnaires and clinical documentation charts), data management and implementation of the study concept. The implementation strategy included three methods—continuous medical education via the quality circle, outreach visits to the hospitals and practices and approaches to local opinion leaders.35
Patients with rectal cancer were identified from hospital electronic data systems and by visits of the study team. To identify migration effects and patients who did not receive in-hospital treatment, doctors' practices in the study area and hospitals in the neighbouring counties were surveyed. Patients who fulfilled the inclusion criteria were informed about the study and received the information leaflet36 from their hospital surgeon before discharge after primary treatment. After obtaining consent, the study team secured primary documentation and contacted the institutions chosen by the patients to do the follow-up, so as to obtain follow-up information. The study team evaluated all clinical data for completeness and consistency, recontacting those who submitted the data when necessary.
Data assessment and analysis
QoL data and clinical data were collected at discharge from the hospital
after primary treatment and at follow-up visits every 3 months over the study
period. QoL was assessed with the self-administered EORTC QLQ-C30 and CR38
questionnaires.4,5,17
Primary documentation of clinical data included sociodemographic details,
standardized clinical and histopathological classification of the
tumour,37 physical
status of the patient and concomitant diseases, diagnostic procedures, nature
of treatment and complications. Follow-up documentation included diagnostic
findings and therapeutic interventions.
To test for an association between compliance with QoL assessment and physical status and treatment in the course of the disease, we applied the methods of correlational studies.38 First, we compared characteristics of the patients who participated in QoL assessment (i.e. those who returned at least one complete questionnaire, n=98) with those who did not (n=48). Second, we analysed two extreme groups—patients who filled in only one or two QoL-questionnaires (poor compliance group, n=20) and patients who filled in all or eight of the nine questionnaires (good compliance group, n=18). These analyses led to the identification of demographic and clinical risk factors for not filling in questionnaires (such as age or tumour stage).
In a third step we analysed whether risk versus no-risk patients differed in the rate of returned questionnaires over the 2-year period and whether the two patient groups differed in the proportion of critical QoL scores over time. On the basis of earlier work9 we defined a score as critical when the value was under 50 on a scale of 0 (very bad) to 100 (very good). For this analysis we chose six QoL scores representative of somatic, psychological and social well-being—physical functioning, role functioning, emotional functioning, future perspective, social functioning and global quality of life. The QoL scores were computed according to the EORTC manual.5
Summary statistics are presented as means and standard deviations,
percentages and graphs over time. The following statistical tests were used:
independent t-test, 
2 test, Pearson correlations. The
two-sided significance level (a) for observed differences was set at 0.05. All
analyses were conducted with SPSS version
10.39
| RESULTS |
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TOPSUMMARYINTRODUCTIONMETHODSRESULTSDISCUSSIONREFERENCES |
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Of the 146 patients fulfilling the inclusion criteria, 98 participated in the QoL assessment and filled in at least one questionnaire during the study period. The remaining 48 did not participate in QoL assessment, for the following reasons: advanced disease (supportive care only, n=5); death within 30 days postoperatively (n=6), refusal to fill in a questionnaire (n=17); physical or mental inability to fill in a questionnaire (n=13). In 7 cases reasons for non-compliance were unclear.
The overall questionnaire response rate was 59% at discharge from the hospital and 36% at the end of follow-up for the cohort (n=146). The mortality rates were 4% (postoperative) and 27% (2 years). Thus, theoretically (taking into account survival) response rates could have reached 94% and 73%, respectively.
Table 1 shows the demographic and clinical details of the cohort and the subgroups of participants and non-participants with QoL assessment. Non-participants were older, were more likely to be receiving palliative (as opposed to curative) treatment, showed greater variance in surgical treatment strategies and were more likely to have American Society of Anesthesiologists (ASA) scores III and IV signifying poor physical status.40
|
Good compliers versus poor compliers
Table 2 compares the
characteristics of good (n=18) and poor (n=20) compliers
with QoL questionnaires as defined above. Poor compliers were older, more
severely ill according to tumour stage and ASA classification and more likely
to receive palliative treatment. The groups differed significantly regarding
therapeutic interventions and progression of tumour disease. In the 2-year
observation period, 9 patients died in the poor-compliance group and none in
the good compliance group; consequently, survival differed significantly from
the time of first operation. Causes of death were progression of tumour
disease in 8 cases and cardiopulmonary disease in 1 case. Clearly, one reason
for the lower responsiveness of poor compliers could have been that they died
sooner; therefore, we looked at individual data. Among the 18 good compliers,
all of whom survived the 2 years, the total possible number of questionnaires
completed was 9618=162. In fact they returned 142 (mean 4 per patient). In the
20 poor compliers mean survival was 8.6 months, so 141 questionnaires (7 per
patient) were in theory returnable until death or the end of follow-up.
Actually they returned only 34 (mean 1.5 per patient). The possible number of
questionnaires in the poor compliance group is almost identical to the number
of questionnaires actually returned by the high compliance group thus, length
of survival is not a sufficient explanation for the difference between these
two groups in number of questionnaires completed.
|
Clinical risk factors for non-compliance
Tables 1 and
2 suggest three main risk
factors for non-compliance—age 475, ASA score III or IV, and palliative
treatment intention. The cut-offs were chosen on the basis of earlier
work.40–43
In the whole cohort 81 patients (55%) presented with one or more of these risk
criteria and thus were assigned to the risk group. The remaining 65 fell into
the non-risk group.
Figure 1 shows the
percentages of patients filling in questionnaires across the 2-year
observation period. Patients in the non-risk group were consistently more
likely to fill in questionnaires than risk patients. Non-risk patients filled
in a total of 276 questionnaires, risk patients a total of 194 questionnaires.
The difference in completion rates (53% versus 30%) was
significant—2 (df=1)=64.71, P<0.001. The
proportions of risk and non-risk patients with score values 550 in selected
domains of QoL are presented in Figure
2. Risk patients were more likely to have critical physical
functioning scores than non-risk patients—27% versus 12%,
2 (df=1)=7.73, P<0.01. Risk patients were more
likely to have critical global QoL scores than non-risk patients—26%
versus 18%, 2 (df=1)=3.49, P<0.06. We also
examined critical score values regarding emotional functioning, role
functioning, social functioning and future perspective, but significant
differences between risk and non-risk patients did not emerge.
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| DISCUSSION |
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TOPSUMMARYINTRODUCTIONMETHODSRESULTSDISCUSSIONREFERENCES |
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The failure to obtain completed questionnaires occurred despite rigorous adherence by the study team to algorithms for data collection and management.36 Recruitment of eligible rectal cancer patients was 100% as indicated by a calculated incidence rate of 22.7/100 000/year and characteristics corresponding to data from the German Cancer Register and population-based studies.44–46
From the methodological point of view, our results indicate that the unobserved data were not missing at random. The risk factors for non-compliance resemble those noted in work from other countries and in patients with different cancers.24,25 The important contribution of the present study is that the risk factors that characterize non-compliant patients are associated with poor scores for QoL. Consequently, application of sample statistics (means, medians) to such data sets may lead to wrong conclusions. This difficulty applies particularly to cross-sectional studies including 'convenience samples' in which the population of origin is not specified, and to cohort studies with high drop-out rates. Any statistical imputation method for missing values has to take into account the strong associations between clinical risk factors, non-compliance with QoL and poor QoL. The handling of missing data should be pre-planned and described in the study protocol.
For clinicians, QoL scores can be valuable in explaining discrepancies between clinical status and wellbeing,47,48 but it is not difficult to think of reasons why severely ill patients are sometimes unkeen to participate in such assessments—lack of concentration, lack of motivation, a move to alternative treatment.10,24 The present study was not designed to disentangle these, but our results could serve as a starting-point for more specific work on the nature of the link. One provocative hypothesis concerns the mooted existence of a 'having fun' stereotype of quality of life. This might cause patients and doctors to believe that QoL is important for the relatively healthy but no longer an issue for the seriously ill. At worst, QoL-related therapeutic interventions11,16,48 might then be withheld in the very patients who stand most to benefit.
| Acknowledgments |
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We thank Susanne Hainbach for management of the data files, computer support and graphical assistance. We are indebted to the members of the quality circle for their valuable comments on practical aspects of regional cancer care and support: U-S Albert, P Berressem, H Böhm, I Dittrich-Scheerer, C Eichler, M Ernst, N Fenner, C Hämmerle, K Fischer, C Heitmann, R Herpers, J Hermanns, A Hochgrebe, M Hoffmann, H Hofmann, M Kuenneke, A Krehbiel, G Leiber, B Marcovici, P Müller, C Nies, J Rosenberger, K-D Schulz, B Städter, B Stinner, F-J Strombach, S Thommes, A Vogel, G-E von Manteuffel, R Weber, F Weidenbach, P Wilke.
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