545 e-Letters

published between 2014 and 2017

  • RE:One misinterpretation

    We thank Mr/Ms Lin for the comments regarding our recent report (Long et al., 2017). We updated a meta-analysis on the association of smoking with NPC risk.
    We agree with Mr/Ms Lin that Lin rightly stated that his/her paper used 'mortality' as the outcome, but the authors reported 'incidence' in the meta-analysis. We have to point out that we did include some valuable articles including Lin’s regarding the mortality or morbidity of NPC to make the review more comprehensive. However, we excluded these in the summary statistics of NPC incidence. For example, we did not Include Lin’s data in Figure 2.

    We agree with Lin in that a meta-analysis of individual participant data (IPD) is needed to clarify the association between smoking and NPC. However, we do not think it is so called “a gold standard”. Instead, we recommend a novel Mendelian randomization analysis (MRA) approach. Using a gene-environment interaction and pathway analysis, we designed MRA to clarify the causal role of environmental exposures such as cigarette smoking in carcinogenesis (Fu et al 2012), because it is always difficult to address or clarify causal-effects by observational studies. We have used this strategy and clarified the causal role of red meat (Fu et al 2012) and cigarette smoking (Fu et al 2013) in pathogenesis of colorectal polyps, the precursors of colorectal cancer. This strategy was highlighted and orally presented in AACR annual meeting 2012 (...

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  • Not a random sample

    Thank you for an interesting paper. The authors claim that women were selected using a systematic random sampling technique. However, their report states that 'The first served pregnant woman and every second woman thereafter were invited to participate in the study until the required sample size was obtained.' This assumes that the women attended the clinic in random order. I they did attend in random order, then selecting every woman consecutively would produce an equally random sample. If there was some pattern to their attendance, then this is not a random sample. I think it would be more accurate to say that this was a convenience sample.

  • Response to comment on statistic

    Thank you for raising this important point. Actually, the Poisson regression is usually used for count data with the variance equal to the mean. And Likert scale data is not suited to this statistic method directly. However, we standardized the scale and the data acquisition for the disability status within 30 days. We assumed that the standardized scores of each domain and summary score (from 0 to 100) as the count of disability status event in 30 days. For analysis the association between the variables of demographic data and standardized WHODAS 2.0 score, we choose the Poisson regression analysis, which could not be perfect for this study. (And the data is near to 1 even statistical significant) Therefore, we didn’t mention the outcome of table 3 in discussion part and conclusion part (merely, mentioned in result part). Our study finding is based on table 2 and we discussed this finding (lower disability status in the WHODAS 2.0 domains of getting along and social participation for patients with dementia with formal education compared with those without formal education) in discussion and conclusion part.

    Thank you again for your precious suggestion. We agree that Multi-level IRT could be an appropriate way to analyze multiple Likert scales. The following studies of original Likert scales of WHODAS 2.0 will be analyzed as your suggestion and this could lead our study to be more convincing.


  • One misinterpretation

    We appreciate this updated meta-analysis on smoking and NPC. However, one misinterpretation of our paper (Lin et al., 2015) was found.
    The paper used 'mortality' as the outcome, but the authors reported 'incidence' in this paper.
    The authors stated, the lack of individual participant data for adjustment of potential confounders. We agree that as a gold standard, a meta-analysis of individual participant data is needed to clarify the association between smoking and NPC.

  • Prediction intervals - the beginning of an effectful future?

    There is considerable debate going on questioning the practical usefulness of a priori power calculations suggesting that “underpowered” studies are not unethical and that little scientific projection would be still better than no projection at all [1-4]. Some authors argue that “being underpowered is unethical” is a “widespread misconception which is only plausible when presented in vague, qualitative terms but does not hold when examined in detail” [1, 2]. Further review of the arguments reveals that the crucial assumptions implied in the reasoning do not reflect actual scientific practice. The main theoretical arguments assume a perfect “frequentist world” that may allow substitution of one big trial by a corresponding number of small trials that would, once being aggregated in a formal evidence synthesis i.e. meta-analysis, cumulate the same information as the big one [2, 4]. If the individual studies are non-representative samples of the target population, the practical value of estimating a pooled effect that is a weighted average of potentially disparate effects in different subpopulations is questionable.

    A widely considered answer to the threat of effect heterogeneity in meta-analyses are random-effect confidence intervals that are often assumed to better reflect variation in the effects across subpopulations than fixed-effects confidence intervals. However, while such intervals offer a valid solution to inference regarding the average effect across all c...

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  • Critical analysis of the Dumont et al. uterine balloon randomized controlled trial in Benin and Mali

    As postpartum hemorrhage (PPH) researchers, and leaders in education and care of maternal health emergencies, from the United States, UK, Canada, India, Peru, Honduras, Zambia, India, Kenya, Tanzania, Colombia and Nepal, we read the Dumont et al paper with great interest. We would like to share our review:

    The most fundamental flaw of this paper is that the authors confuse an intention-to-treat study of a clinical pathway of interventions and behaviors, with the efficacy of a device. These are two very different research questions. In order to test the latter via a randomized controlled trial (RCT) the two groups would need to be the similar and subjects that did not even receive the device (or received it in desperation two hours after the diagnosis of uncontrolled PPH) certainly could not be included in the intervention group. Thus, this study attempts to test intention-to-treat, not the efficacy of the uterine balloon tamponade (UBT) device.

    The second most obvious flaw is that degrees of illness are not accounted for. Clinically defined "uncontrolled PPH" is in no way a homogeneous group. For example, someone that has been referred in and is moribund from their advanced shock is an entirely different subject than someone who has mild uncontrolled PPH. Since this is not controlled for, these two groups are likely incomparable.

    Even taking into account the two issues described above, the two groups are different and heavily favor the non-...

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  • Breast cancer mortality is associated with factors linked to social and medical development in São Paulo State, Brazil

    Dear Editor:
    We have read the study conducted by Diniz et al. on the possible association between mammography and breast cancer-related mortality in the state of São Paulo, Brazil with the greatest of care. Despite the detailed statistical analysis, the ecological study design implies limitations to the hypothesis generated, as pointed out by the authors themselves (1). In our opinion, both the authors’ main conclusion and the assumed association of cause and effect are inappropriate.

    The factors associated with the incidence of breast cancer in Brazil and its resulting mortality have recently been evaluated in different studies (2-4). Mortality rates have been found to vary as a function of geospatial location (rural areas versus urban centers)(4). In addition, the reduction encountered in mortality was associated with the regions in which the human development index (HDI) was higher. On the other hand, the highest mortality rates have been found to occur in the states with the highest HDI (5). Diniz et al. and many other investigators have mentioned that a higher incidence of breast cancer occurs among more affluent women living in urban areas and in large cities (1,5). In this respect, we are certain that mortality is also related to the incidence of the disease; hence, the higher the incidence, the greater the resulting mortality will be. Conversely, women who do not have breast cancer will obviously not die from the disease.

    Therefore, we believe t...

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  • Cholesterol levels have negligible correlations with cardiovascular events

    Please see my article with the above name, published in the New Zealand Medical Journal, which used the Caerphilly data. This has not been mentioned elsewhere, presumably because of its obscure site. There was no relationship at all between cholesterol and heart attacks and only 4% of the variance was associated with strokes. NZ Med. J. 2012, 125, 1364.

  • Ask not only whether unpublished data were used but also how they were used

    This study asks the important question, what proportion of systematic reviews searched for and made use of unpublished data? However, an important follow-up question remains to be addressed: Among those cases in which unpublished data was used, how was it used? Unpublished data can of course address study publication bias, ie. data from unpublished studies can be simply added to data obtained from the published literature. However, unpublished data can also address outcome reporting bias,[1-3] ie. a trial publication conveys that the intervention is safe and/or effective while unpublished data on the same trial tell a different story. For example, in a study of 74 industry-sponsored antidepressants trials,[4] in addition to 23 (31%) unpublished trials, we found 11 (15%) trials with outcome reporting bias. If we had corrected for the former while ignoring the latter, we would have obtained an effect size estimate that was still inflated. Returning to the current study,[5] an informative follow-up would be to look within the cohort of systematic reviews that made use of unpublished data and determine how many used it to verify the published results.


    1 Kirkham JJ, Dwan KM, Altman DG, et al. The impact of outcome reporting bias in randomised controlled trials on a cohort of systematic reviews. BMJ 2010;340:c365.

    2 Chan A-W, Altman DG. Identifying outcome reporting bias in randomised trials on PubMed: review of publications and survey of author...

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  • Authors respond to "Comments on PROMISE data interpretation in Siemieniuk meta-analysis from PROMISE team"

    Dear Editor:

    We thank Dr. Fowler and colleagues for taking the time to consider and comment on our BMJ Rapid Recommendation (1). They speculate on reasons why tenofovir and emtricitabine increased the risk of neonatal mortality and early preterm delivery in their trial (2) and then say that the current evidence does not support a recommendation for alternative NRTIs over a tenofovir-based antiretroviral therapy (ART) regimen. We do agree that most, but not all, of the evidence comes from a single study, which may have overestimated harm. Our systematic review attempted to generate the current best evidence, and is not definitive: it is moderate-to-low quality for key outcomes (3). However, we disagree with the implication that based on this evidence, most women would choose a tenofovir-based ART regimen.

    The PROMISE authors suggest that results of the comparison between tenofovir-ART and AZT-ART are untrustworthy because the risk of neonatal death was lower in the AZT-ART arm in the earlier period 1 before the tenofovir-ART arm was introduced (2). However, the difference between the two time-periods in the AZT-ART arm could easily be explained by chance (neonatal mortality 1.4% in period 1 vs. 0.6% in period 2, p=0.39; very preterm delivery 3.4% in period 1 vs. 2.6% in period 2, p=0.60). Regardless, the only reliable comparison between tenofovir-ART and AZT-ART is during period 2 when randomisation to both AZT and tenofovir-based ART occurred. Despite these r...

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