Previous comments to manuscript 1023433087733316
Reviewer's report
Title: Association between geographic remoteness, area disadvantage and colorectal cancer survival: a cross-sectional
multilevel study.
Version: 1 Date: 13 July 2012
Reviewer: David Morrison
Major Compulsory Revisions - MCR Minor Essential
Revisions – MER
Discretionary Revisions- DR
Is the question posed by the authors well defined?
1. I think the question needs to be made clearer. On first reading this manuscript, I thought the authors were going to
use individual-level measures of socio-economic status as well as ecological measures of area disadvantage and
remoteness. But if I’ve understood it correctly, they use an ecological measure of socio-economic circumstances (IRSD)
plus individual-level clinical and demographic information (a combination that forms the basis for much of the
published research on socio-economic circumstances and colorectal cancer survival) and added an area-level measure
of geographic remoteness. The Abstract and Introduction would be improved with a clearer focus on the question of
whether geographic remoteness is associated with survival after colorectal cancer surgery, after adjusting for other
known risk factors. [MER]
Response: The cohort for the study is no longer restricted to only who had surgery. However we have focused the
Abstract and Introduction on the question of whether geographic remoteness is associated with survival outcomes for
colorectal cancer patients.
2. The main conclusion, I believe, is that living in a remote and rural area is associated with poorer survival after
colorectal cancer surgery. This should be stated in the Abstract. [MER]
Response: The Abstract now states that patients from remote areas had lower CRC-specific survival than major cities.
Are the methods appropriate and well described?
3. All cause mortality should be given as well as cancer-specific mortality. The authors note that death records may be
more inaccurate at older ages but their validity for determining cause-specific deaths is not very good at all ages.
[MCR]
Response: We have analysed both all-cause and CRC-specific survival.
4. On a related point about cause-specific mortality, relative survival is increasingly the preferred way of inferring
cancer-specific deaths. The authors should consider if this could be used in their models. [DR]
Response: To the best of our knowledge, relative survival models incorporating a full multilevel framework have not
been described in the literature. Bayesian spatial models, using aggregated data are available for relative survival. In
separate analyses (not reported in this manuscript) we have found similar associations between geographic
remoteness, disadvantage and relative survival as reporting in our current paper.
5. Patients aged over 79 years are excluded. In the UK, this comprises over 30% of colorectal cancer patients. I would
recommend including patients at least up to 85 years of age. All cause mortality data should not be any less valid at
older ages. [MCR]
Response: Our cohort now includes patients up to 84 years of age at diagnosis.
6. I would recommend removing ICD-21.8 cancers from this analysis. Their inclusion is unusual in a study of colorectal
cancer survival, because their treatment and survival patterns are rather different. [MER]
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Response: In line with our previous studies on colorectal cancer survival, and standard cancer registry reporting
practices, we have retained ICD-21.8 cases in our cohort. It should be noted that such cases comprise less than 0.5% of
our cohort. Also the parameter estimates were similar when final models were repeated after removing these cases.
Are the data sound?
7. In the Results, more consideration should be made to the significant differences between included and excluded
patients. It would be interesting to see what determines inclusion/exclusion in a multivariable binary logistic
regression. The conclusions of such an adjusted analysis could give important insights into whether the apparently
lower rates of surgery in more deprived populations can be explained by the casemix data that are available. [MER]
Response: This point is no longer relevant as we no longer restricted our study to surgically treated patients only.
8. In the Discussion, also, more consideration should be made of the possible selection biases that may have occurred.
For example, 11.3% of the least disadvantaged were excluded compared with 14.5% of the most disadvantaged. So on
top of the persisting geographic and socio-economic differentials in survival reported in the multivariable models on
surgical patients, there is the population-level impact of more disadvantaged patients not being given surgery. [MER]
Response: This point is also no longer relevant as we no longer restricted our study to surgically treated patients only.
Does the manuscript adhere to the relevant standards for reporting and data deposition?
9. No particular issues arise in this area.
Are the discussion and conclusions well balanced and adequately supported by the data?
10. The Discussion should elaborate on the practical implications of this work. I wonder if this analysis is describing
variations in hospital outcomes that might be related to case volume and surgical specialisation, because city and
remote hospitals are likely to differ with respect to these? If the authors think this is a fair hypothesis, it would be
worth suggesting in the Discussion/Conclusions that this is a line of further investigation that should be pursued.
[MER]
Response: These points have now been included in our discussion
11. The Discussion should return to the differentials in surgery across different groups and consider how these might
be better understood. Again, the implications for public health are important because they may suggest that patients
are presenting with more advanced disease, or they may suggest that inequities in surgical intervention rates exist, or
a mixture of the two. [MER]
Response: Please refer to Points 7 and 8, in that the surgical information is no longer included in this study.
12. See also comment 8.
Are limitations of the work clearly stated?
13. This section should include reference to selection biases of the surgical cohort. If all-cause mortality is included,
which I strongly suggest it should be, the limitation about cause-specific survival can be removed. [DR]
Response: We have analyzed both all –cause and CRC-specific survival. Since this is now a population-based study of
all persons who were diagnosed with primary invasive CRC the issue of selection bias for the surgical cohort is no
longer relevant.
Do the authors clearly acknowledge any work upon which they are building, both published and unpublished?
14. Appropriate references to the major recent analyses of socio-economic circumstances and colorectal cancer
survival have been provided.
Do the title and abstract accurately convey what has been found?
15. I suggest that the title should indicate that the analysis describes colorectal cancer “after surgery” as it is not a
population-based study. [DR]
Response: Our study is now a population-based study as it is no longer restricted to surgically treated CRC patients
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only.
Is the writing acceptable?
16. Yes.
Level of interest: An article whose findings are important to those with closely related research interests
Quality of written English: Acceptable
Statistical review: Yes, but I do not feel adequately qualified to assess the statistics.
Reviewer's report
Title: Association between geographic remoteness, area disadvantage and colorectal cancer survival: a crosssectional multilevel study.
Version: 1 Date: 21 August 2012
Reviewer: Mario Schootman
The purpose of this study is to examine the association between geographic remoteness, area disadvantage and
colorectal cancer (CRC) survival in Queensland, Australia. The significance of the study is based on the focus on
CRC, the population-based nature of the data, and the use of a multilevel to discriminate between individual and
area-level factors. However, there are several weaknesses to the study as well.
MAJOR ISSUES
1. The Introduction focuses a lot on the importance of using a multilevel statistical analysis to discriminate between
individual and area-level variance. While this is important to do in a study such as the one that is reported in the
manuscript, this is not very innovative. This has now become more or less standard practice in area-level studies. It
might have been better to focus the Introduction on the importance of area-level factors, why the authors hypothesize
the two factors to be associated independently with CRC survival, and what the potential implications are for public
health and/or clinical practice.
Response: The Introduction has been modified accordingly. In addition to the multilevel methodology we have used
measures such as the presented median odds ratios to describe the magnitude of unexplained geographical variation
in a more meaningful way, and the interval odds ratios to integrate the area-level fixed and random terms.
2. The authors state that “unless studies of area-level factors also adjust for individual-level factor, the interpretation
of those factors may be compromised.” However, this depends on the purpose of the analysis. Adding variables to a
statistical model is different when examining mediation versus confounding.
Response: The introduction has been modified accordingly
3. The authors focus their aims, sections of the Results and Discussion on the results of the individual-level factors.
Their results are not very innovative compared to previous studies. It is somewhat unclear what these findings add to
the existing literature from other countries.
Response: We have focused our studies on the area-level factors and the implications of our findings with particular
relevance to the Australian context.
4. No information was provided about why these individual-level factors were selected. Is this based on a conceptual
model?
Response: We included all available individual level factors from the population-based cancer registry and then added
in additional clinical information extracted from pathological forms.
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5. Little information was provided about how the area-level disadvantage variable was constructed, variables
examined, Crohnbach's alpha, factor loadings, etc. Also, were the quintiles of the IRSD score based on the number of
SLAs or the number of CRC patients? This may affect the results.
Response: This is a published measure of area disadvantage which is used as a standard measure of area
disadvantage in Australia.
6. A difference of at least 7 for the DIC is typically considered an improvement in models.
Response: All model comparisons are now based on DIC criterion of 7 units.
7. The remaining area-level variance is very small (~1%) after entering the individual variables and may not be very
important relative to the rest of the variance. The authors should discuss the fact that this variance is very small and
becomes nonsignificant after entering the area-level factors while the latter types of variables are statistically
associated with survival. Although the authors state that “a clear gradient or poorer survival,” the 95% CI are very wide
and nearly completely overlapping. This “clear gradient” may be overstating the findings.
Response: We have discussed the fact that the area-level variance is very small and became non-significant after
adjustment for area-level factors. We are no longer using the term ‘clear gradient’ to discuss our findings.
8. Many other individual-level factors have been associated with worse CRC prognosis and might explain their arealevel findings, such as stress, (epi)genetic changes, inflammation, oxidative stress, surveillance following diagnosis but
are not discussed.
Response: These have been included as potential factors in our discussion.
9. In some instances the authors try to explain their findings but seem to disregard their own results. For example,
they state that indigenous people have lower screening and comorbidity. This is not pertinent since comorbidity was
included in their statistical model.
Response: This is no longer relevant as we no longer included comorbidities in our analyses.
10. It would be important to go beyond simply stating what the study's limitations are and describe if they can explain
their findings.
Response: We have focused our discussion on the possible explanations and practical implications of our findings.
11. It is unclear how the authors calculated their main effects for the area-level remoteness and ISRD for model 6 in
Table 2 since interactions were included.
Response: On the basis of the DIC criteria, the main effects model was the best fitting model. There was no evidence
for interactions between area-level terms being significant. Therefore all fixed effects are presented for the main
effect s model only, so this comment is no longer relevant.
MINOR ISSUES
12. Previous studies typically have used the Charlson or Elixhauser comorbidity scale. It is somewhat curious why the
authors only focused on selected comorbidities (page 5).
Response: No comorbidities have been included in the current study
13. There was only one value listed in Table 2 for the 95% CI.
Response: This is no longer relevant as the Tables have been substantially revised.
Level of interest: An article of limited interest
Quality of written English: Acceptable
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Statistical review: No, the manuscript does not need to be seen by a statistician.
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