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We recently reported on brain tumour incidence time trends in 20 to 59 year old Australians, from 1982 to 2013, and analysed these in terms of mobile phone usage patterns and diagnostic improvements over that interval1. This was designed to determine whether claims that mobile phone use causes brain tumours, are consistent with the pattern of brain tumour incidence in Australia, and in particular to compare such incidence patterns with the results of the multinational Interphone case control study2. In summary, we reported that: 1/ Overall brain tumour incidence rates did not change over time; 2/ Increased glioblastoma incidence was seen during intervals that coincided with improvements in diagnostic technologies (CT, MRI); 3/ Decreased incidence of ‘unspecified’ tumours was seen during the same intervals; and 4/ No evidence of increased tumour incidence (including glioblastoma) related to mobile phone use was found (based on incidence rates seen during the period of substantial mobile phone use and on modelling using a range of hypothetical relative risks and latency periods).
Philips submitted a Letter to the Editor3 of BMJ Open, where he purports to show that there are ‘significant flaws and unjustifiable conclusions’ in the above paper. Although he may firmly hold this view, his letter does not provide any evidence of this, and we strongly disagree with his statement. We have addressed the substance of his letter below to hopefully obviate potential misunderstan...
We recently reported on brain tumour incidence time trends in 20 to 59 year old Australians, from 1982 to 2013, and analysed these in terms of mobile phone usage patterns and diagnostic improvements over that interval1. This was designed to determine whether claims that mobile phone use causes brain tumours, are consistent with the pattern of brain tumour incidence in Australia, and in particular to compare such incidence patterns with the results of the multinational Interphone case control study2. In summary, we reported that: 1/ Overall brain tumour incidence rates did not change over time; 2/ Increased glioblastoma incidence was seen during intervals that coincided with improvements in diagnostic technologies (CT, MRI); 3/ Decreased incidence of ‘unspecified’ tumours was seen during the same intervals; and 4/ No evidence of increased tumour incidence (including glioblastoma) related to mobile phone use was found (based on incidence rates seen during the period of substantial mobile phone use and on modelling using a range of hypothetical relative risks and latency periods).
Philips submitted a Letter to the Editor3 of BMJ Open, where he purports to show that there are ‘significant flaws and unjustifiable conclusions’ in the above paper. Although he may firmly hold this view, his letter does not provide any evidence of this, and we strongly disagree with his statement. We have addressed the substance of his letter below to hopefully obviate potential misunderstandings that his letter may generate.
1/ A substantial portion of the Letter is dedicated to describing aspects of a paper published by Philips and colleagues4. Philips does not relate that description to Karipidis et al. (2018)1, and as his restatement of his paper does not raise any issues that were not considered in our work, we do not comment on that here.
2/ There are a number of factual inaccuracies in Philips’ letter.
For example, in relation to our report of an increased incidence in glioblastoma over the 1993-2002 period, he claims that Karipidis et al. concluded that it “was due to diagnostic improvements”. If Philips was correct, we would agree that this would represent an oversimplification of the data. However, we have been very careful to appropriately interpret the results and the level of certainty the evidence provided from the analyses; indeed we stated that the elevated glioblastoma incidence from 1993 to 2002, with no significant increase from 2003 to 2013, was “most likely due to improved diagnosis from MRI” (p. 10). Further, in support of this we gave substantial reasons for why diagnostic improvements are a far more likely explanation than radiofrequency exposure from mobile phone use.
Similarly, Philips’ letter says that “Karipidis et al incorrectly state that we did not analyse different time periods to investigate the impact of mobile phone use”, and then goes on to show that different time periods were reported separately. However, our statement is correct in that, although some breakdown of time periods was given, these time periods do not correspond to periods relevant for determining whether incidence changes were related to mobile phone use (such as intervals relating to diagnosis change or mobile phone usage patterns), and no data is provided to address the issue of mobile phone use. Indeed Philips et al. did not even claim to have addressed cancer incidence in terms of mobile phone use specifically, and Karipidis et al. has merely noted this.
3/ Philips asks how rapidly developing tumours can be misdiagnosed and recorded. This has been dealt with in our paper, which includes consideration of the fact that there is no increase in glioma overall, that the increase in glioblastoma is paralleled by a reduction in ‘unspecified’ tumours, that the increase in glioblastoma incidence occurs during a period of improved diagnosis and changes to the tumour classification scheme, and that it precedes the period of rapid mobile phone use. Further, Philips does not provide any argument for his apparent view that we are erroneous in our conclusion that the temporary rise in glioblastoma incidence is most likely due to improved diagnosis and classification.
4/ Philips states that changes in antenna position on different phones, and different communication technologies (e.g. 2G, 3G, 4G) “should have been discussed by Karipidis et al.” However, Karipidis et al. states that we could not take changes in technology and patterns of individual use into account, as we had no representative data on the effects of such changes on individual exposure; and discussion could thus be no more than speculation.
5/ Philips’ letter criticised our paper for assessing data for 20-59 year olds, rather than for all ages. Although Philips may see benefit in conducting a study quite different to ours, there are many benefits in the method that we used, and these were described in Karipidis et al. For example, our study was designed to compare cancer incidence with that that would be expected based on different interpretations of the Interphone2 results, and this is the age range used in the Interphone study (which in turn was chosen to “maximise the likelihood of exposure”5). Beyond that, more-general methodological considerations point to the appropriateness of this age range: 1/ As cases older than 60 would be more affected by the diagnostic issues described above, 60+ year olds were not included as their inclusion would reduce the chance of seeing mobile phone related changes to tumour incidence; 2/ As we wanted to test whether tumour onset latencies of > 10 years could explain observed tumour incidence rates, and as this would require cases < 20 years old to have substantial mobile phone usage before the age of 10 (which they do not), those < 20 were not suitable for the purposes of this study. The relatively small number of cases in the < 20 year age group (being far rarer than in adults), would also increase data instability, making it less likely to observe meaningful changes in tumour incidence.
6/ Philips criticises Karipidis et al. for using the World Health Organization’s (WHO) world standard population to standardize our data, as he believes that a different method should have been sought. However the purpose of this standardisation is to ensure age-comparability of each year’s data, and the WHO world population provides comparability with much of the international literature, which is very useful in addressing this issue. We do not believe that the use of other standards would change the time trends appreciably.
7/ It is noteworthy that Philips is the Technical Director of a company that derives income from selling devices which were “mainly designed by Alasdair Philips”, “to protect people from the ever-increasing levels of Electromagnetic radiation, or electrosmog, in our environment” (https://emfields-solutions.com/aboutus.asp). Thus although he fails to declare any conflict of interest in relation to his letter, this activity would normally be seen as a direct conflict of interest; whether radiofrequency exposure due to mobile phone use is seen as being related to cancer induction or promotion would have a tangible effect on whether people purchased devices to ‘protect’ themselves from such radiofrequency exposure.
In conclusion, Philips’ Letter to the Editor does not raise any cogent issues with Karipidis et al. Instead it provides a series of claims that Karipidis et al. is inadequate, but does not provide relevant argumentation in support of this. We maintain that the data presented in Karipidis et al. does not provide any indication of mobile phone-related increases in cancer incidence, but conversely that it does suggest that changes to glioblastoma diagnostic and classification practices in Australia are a more likely explanation for the reported increase in glioblastoma incidence rates in Australia.
References:
1. Karipidis K, Elwood M, Benke G, Sanagou M, Tjong L, Croft RJ. Mobile phone use has not increased the incidence of brain tumour histological types, grading or anatomical location: A population-based ecological study. BMJ Open, 2018, 8(12):e024489.
2. INTERPHONE Study Group. Brain tumour risk in relation to mobile telephone use: results of the INTERPHONE international case-control study. Int J Epidemiol, 2010(39):675–94.
3. Philips A. Significant flaws and unjustifiable conclusions. Letter to the Editor, BMJ Open, 2019.
4. Philips A, Henshaw DL, Lamburn G, et al. Brain tumours: rise in Glioblastoma Multiforme incidence in England 1995–2015 suggests an adverse environmental or lifestyle factor. J of Environment and Public Health, 2018:7910754.
5. Cardis E, Richardson L, et al. The INTERPHONE study: design, epidemiological methods, and description of the study population. Eur J Epi, 2007, 22(9):647-664.
We have read with interest the article by Ball et al (2018) recently published in BMJ Open and note that they refer to our letter (Pereira Gray and Wilkie, 2017) which listed disadvantages of this system from the point of view of patients and where we reported the opposition of the National Association of Patient Participation (N.A.P.P.) to this system.
We agree with the authors that ‘telephone first’ system is a “fundamental” change in the provision of general practice.
The authors refer in detail to the independent review of this system Newbould et al (2017), which was published on the BMJ in 2017 and in which three of the authors were the same. We are puzzled by the way they summarise it.
Authors’ statements in 2018 can be contrasted with the published results in Newbould et al 2017. For example, Ball et al write “No evidence of reduced secondary care costs.” Whereas Newbould et al wrote “we found a significant increase of cost of admissions… leading to an estimated overall increase in secondary care costs of £11,766 per 10,000 patients (i.e. over £1 per patient registered in the general practices).
Secondly, Ball et al write “Little overall improvement in patient satisfaction as expressed in patient surveys” when Newbould et al reported:
1.GP communication composite-Significant fall (P<0.001)
2. Would you recommend your surgery?- Significant fall (P<0.001) 3.Seeing preferred GP- Significant fall (P<0.035)
We have read with interest the article by Ball et al (2018) recently published in BMJ Open and note that they refer to our letter (Pereira Gray and Wilkie, 2017) which listed disadvantages of this system from the point of view of patients and where we reported the opposition of the National Association of Patient Participation (N.A.P.P.) to this system.
We agree with the authors that ‘telephone first’ system is a “fundamental” change in the provision of general practice.
The authors refer in detail to the independent review of this system Newbould et al (2017), which was published on the BMJ in 2017 and in which three of the authors were the same. We are puzzled by the way they summarise it.
Authors’ statements in 2018 can be contrasted with the published results in Newbould et al 2017. For example, Ball et al write “No evidence of reduced secondary care costs.” Whereas Newbould et al wrote “we found a significant increase of cost of admissions… leading to an estimated overall increase in secondary care costs of £11,766 per 10,000 patients (i.e. over £1 per patient registered in the general practices).
Secondly, Ball et al write “Little overall improvement in patient satisfaction as expressed in patient surveys” when Newbould et al reported:
1.GP communication composite-Significant fall (P<0.001)
2. Would you recommend your surgery?- Significant fall (P<0.001) 3.Seeing preferred GP- Significant fall (P<0.035)
Why have the authors summarised Newbould et al. by twice writing that there was “ no evidence or little overall improvement” when Newbould et al. provided important evidence that telephone-first system is associated with increased costs for the general practices (which pay for the system), increased costs for the hard-pressed hospital service, and significantly worse satisfaction for patients on three key questions?
Ball et al support the conclusion of the ESTEEM study, which also used telephone triage, “there is considerable potential in using telephone consultations in general practice”, but omit the important consequence that GP triage in that study was associated with a 22% increase in the use of out-of-hours services by patients - a bad outcome for patients (Pereira Gray and Wilkie 2015; Campbell et al., 2015).
The patients’ actions in the ESTEEM study and their responses to the 2017 study have not been properly valued. We appreciate the need to explore methods of making the most appropriate and cost-effective use of GP time. However, N.A.P.P. believes that there is a real need to independently evaluate the various uses of this service before they are more widely introduced.
References
Ball SL Newbould J Corbett J et al Qualitative study of patient views on a ‘telephone-first’ approach in general practice in England: speaking the GP by telephone before making face to face appointments BMJ Open 2018; 8 :e026197
Campbell J Warren F Taylor R et al (2015) Authors’ reply Lancet 2015; 385 :688
Newbould J Abel G Ball S et al. (2017) Evaluation of telephone first approach to demand management in English general practice: observational study BMJ 2017; 358 : j4197
Pereira Gray D and Willkie P Patient perspectives on telephone triage in general practice [Letter] Lancet 2015; 385: 687
Pereira Gray D and Wilkie P Patient perspectives on telephone first system BMJ 2017; 359 :j4925
This is a useful study. May I suggest that the Output Area Classification (OAC) offers similar insights based on social groupings. Several studies have explored the use of the OAC relating to A&E attendance and Critical Care admission [1-3]. I suspect that your data is amenable to further helpful analysis using the OAC.
1. Beeknoo N, Jones R. Factors influencing A&E attendance, admissions and waiting times at two London hospitals. British Journal of Medicine and Medical Research 2016; 17(10): 1-29. doi : 10.9734/BJMMR/2016/28783
2. Beeknoo N, Jones R. Using Social Groups to Locate Areas with High Emergency Department Attendance, Subsequent Inpatient Admission and Need for Critical Care. British Journal of Medicine and Medical Research 2016; 18(6): 1-23. doi: 10.9734/BJMMR/2016/29208
3. Beeknoo N, Jones R. Using social groups to locate areas of high utilization of critical care. BBritish Journal of Healthcare Management 2016; 22(11): 551-560.
I worked on emergency ambulances in London from 1974 to 1978. I attended several bomb calls during the IRA campaign and it was terrifying to sit in a fibreglass ambulance knowing that there was a real risk of being right next to a car bomb that might be detonated with the intention of harming the emergency services. I was 19 at the time. Looking back, with my current knowledge, I can see that the experience was quite harmful for me. In addition to the existential threat there was also the fear of failing to perform and letting people down and being seen to be a coward. This also took its toll.
Other things also took a toll and they were not so obvious. Dealing with sick elderly patients was incredibly depressing. I came to fear growing old, because the only old people that I was meeting were ill and depressed and really not enjoying life. I saw so many old people living sad lives in grinding poverty.
Again, with maturity, this seems totally absurd, but as a 19 year old with no experience of healthy older people (my grandparents were all dead) ambulance work made me very sad. I was surrounded by other ambulance workers who I think tended to be able to cope by having sociopathic tendencies. A very toxic milieu!
My point here is that when I compared notes with ambulance workers with similar seniority in more rural settings and away from the IRA bombs, their experiences were entirely different. They attended the occasional serious RTC, but mos...
I worked on emergency ambulances in London from 1974 to 1978. I attended several bomb calls during the IRA campaign and it was terrifying to sit in a fibreglass ambulance knowing that there was a real risk of being right next to a car bomb that might be detonated with the intention of harming the emergency services. I was 19 at the time. Looking back, with my current knowledge, I can see that the experience was quite harmful for me. In addition to the existential threat there was also the fear of failing to perform and letting people down and being seen to be a coward. This also took its toll.
Other things also took a toll and they were not so obvious. Dealing with sick elderly patients was incredibly depressing. I came to fear growing old, because the only old people that I was meeting were ill and depressed and really not enjoying life. I saw so many old people living sad lives in grinding poverty.
Again, with maturity, this seems totally absurd, but as a 19 year old with no experience of healthy older people (my grandparents were all dead) ambulance work made me very sad. I was surrounded by other ambulance workers who I think tended to be able to cope by having sociopathic tendencies. A very toxic milieu!
My point here is that when I compared notes with ambulance workers with similar seniority in more rural settings and away from the IRA bombs, their experiences were entirely different. They attended the occasional serious RTC, but mostly their calls were somehow nicer. I went on to experience this in rural France later on.
I applaud the study and hope that it will be the first of many and that its findings will be acted upon. However, to improve the case pick-up rate, I wonder whether it would be worth considering gathering information on the subjects' contact with psychologically traumatic events. It might also be worth considering an exploration of the sociological stresses that they encounter and their view of more experienced colleagues' coping strategies.
Karipidis et al report that in Australia, glioblastoma (GBM) incidence increased significantly only during the period 1993-2002. They conclude that this was due to diagnostic improvements and that there has been no increase in any brain tumour histological type or glioma location that can be attributed to mobile phones.
I am lead author of an ecological study published early in 2018 that examined detailed underlying incidence trends for 81,835 biologically malignant (ICD10 C70) brain tumours, recorded in England over the period 1995-2015 [1]. Karipidis et al cite our study and note that we reported that the overall incidence of GBM more than doubled over that time period (from 2.4 to 5.0 per 100,000 person years, age-standardised to the European Standard Population ESP2013, with annual case numbers rising from 983 to 2531). Zada et al (2012) [2] and Ho et al (2014) [3] have reported similar trends.
Although we briefly discussed five possible causal factors that might have contributed to the rise in incidence, we stated that our article reported incidence data trends and did not provide additional evidence for the role of any particular risk factor. We showed that most of the rise in incidence was in people over 55 years of age. We discussed the possible mix of promotion of lower grade tumours and de-novo tumours. We also discussed the effect of better imaging and more accurate diagnosis and concluded that although it did have an effect, especially for topogra...
Karipidis et al report that in Australia, glioblastoma (GBM) incidence increased significantly only during the period 1993-2002. They conclude that this was due to diagnostic improvements and that there has been no increase in any brain tumour histological type or glioma location that can be attributed to mobile phones.
I am lead author of an ecological study published early in 2018 that examined detailed underlying incidence trends for 81,835 biologically malignant (ICD10 C70) brain tumours, recorded in England over the period 1995-2015 [1]. Karipidis et al cite our study and note that we reported that the overall incidence of GBM more than doubled over that time period (from 2.4 to 5.0 per 100,000 person years, age-standardised to the European Standard Population ESP2013, with annual case numbers rising from 983 to 2531). Zada et al (2012) [2] and Ho et al (2014) [3] have reported similar trends.
Although we briefly discussed five possible causal factors that might have contributed to the rise in incidence, we stated that our article reported incidence data trends and did not provide additional evidence for the role of any particular risk factor. We showed that most of the rise in incidence was in people over 55 years of age. We discussed the possible mix of promotion of lower grade tumours and de-novo tumours. We also discussed the effect of better imaging and more accurate diagnosis and concluded that although it did have an effect, especially for topography, it was small as regards overall GBM incidence as the tumours are very aggressive and the prognosis so poor. In short, how can you misdiagnose and record a rapidly fatal tumour?
Karipidis et al incorrectly state that we did not analyse different time periods to investigate the impact of mobile phone use. Our Figure 4 shows the relative change in GBM age-specific incidence rates (ASpR) averaged over two five-year periods 1995-1999 and 2011-2015, in 5-year age bands and gender, though this was not done specifically to test for the impact of mobile phone use. The underlying data for the whole period (1995-2015), as case numbers and as age-specific incidence rates, by year and by age-group, is set out in our Supplementary File (Tables S2) which was published alongside our article [4]. If you analyse the slopes in incidence for the periods 1995-2002 and 2003-2013 they are similar and both highly statistically significant. The later period incidence rate rises more slowly (AAPC 3.5%, 95% CI 2.8-4.2, p<0.0001). This would be expected if it were related to mobile phone use, since by 2006 the antenna position moved from the top to the bottom of most handsets, closer to the thyroid than the brain, and people were more commonly texting and using a hands-free mode. This confounder, along with changes in technology (i.e. GSM->3G->4G) should have been discussed by Karipidis et al.
Importantly, Karipidis et al only report on brain tumour data for ages 20-59. This represents about 39% of Australian brain tumours (c. 6% of cases are under age 20 and c. 55% are aged over 59). Given especially that Interphone and other studies have reported that long-term use and latency are important factors, it is inappropriate to exclude the group of people (a) who will generally have used their phones for the highest number of years, and (b) who are also the age-group who already had the highest incidence of brain tumours.
In addition, Karipidis et al age-standardised their data to the World Health Organisation's (WHO) world standard population, which in no way represents the modern Australian population age-spectrum. It over-weights young ages and significantly under-weights ages over 45. If age-standardised (rather than age-specific) data is to be used when investigating modern trends in a current population, then the standard population spectrum used should reasonably match the current actual population - especially with the current rapid increase in elderly people. We discuss this issue in some detail in our Letter to the Editor which was published alongside our article. [5]
The Australian and English population age spectra are very similar, as are the brain tumour incidence rates with age-group. The conclusions of Karipidis et al without strong caveats are therefore unjustified. In my opinion, their article unreasonably and misleadingly distorts the literature on modern detailed brain tumour incidence trends. The fact that it passed peer-review raises questions as to the competence and independence of the review process.
We write to express our concern about the prevalence estimate of plagiarism in African medical journals in the study reported by Rohwer et al.(1) The authors’ finding that 63% of African medical journal articles are plagiarized to some degree is a gross overestimate.
The study definitions of “some,” “moderate,” and “extensive” plagiarism are unvalidated and, as the authors admit in the fourth paragraph of their Discussion section, lack inter-rater reliability and precision. Articles were classified as having “some” plagiarism if there were as few as 1-2 sentences that included identical words or sentences in another article by different authors even if the sentences were properly referenced. Numerous publishing organizations, including the Council of Science Editors,(2) the World Association of Medical Editors,(3) and the US Office of Research Integrity,(4) reserve the use of plagiarism for instances when another’s words are used without proper credit or attribution. The authors developed their definition based on suggestions from the Committee on Publication Ethics (COPE), yet even COPE’s Flowchart for managing suspected plagiarism in a submitted manuscript defines plagiarism as “unattributed use of large portions of text and/or data.”(5)
In fairness to the African journals implicated in the study, we request the authors go back to their data, identify all instances in which identical wording with formal source citations were defined as plagiarism, recalcu...
We write to express our concern about the prevalence estimate of plagiarism in African medical journals in the study reported by Rohwer et al.(1) The authors’ finding that 63% of African medical journal articles are plagiarized to some degree is a gross overestimate.
The study definitions of “some,” “moderate,” and “extensive” plagiarism are unvalidated and, as the authors admit in the fourth paragraph of their Discussion section, lack inter-rater reliability and precision. Articles were classified as having “some” plagiarism if there were as few as 1-2 sentences that included identical words or sentences in another article by different authors even if the sentences were properly referenced. Numerous publishing organizations, including the Council of Science Editors,(2) the World Association of Medical Editors,(3) and the US Office of Research Integrity,(4) reserve the use of plagiarism for instances when another’s words are used without proper credit or attribution. The authors developed their definition based on suggestions from the Committee on Publication Ethics (COPE), yet even COPE’s Flowchart for managing suspected plagiarism in a submitted manuscript defines plagiarism as “unattributed use of large portions of text and/or data.”(5)
In fairness to the African journals implicated in the study, we request the authors go back to their data, identify all instances in which identical wording with formal source citations were defined as plagiarism, recalculate their plagiarism estimates with instances of proper attribution excluded, and formally correct their article. Only then will the study estimate be credible and useful to the journals included in this study.
Moreover, the singling out of 7 journals from the African Journal Partnership Program (AJPP) is unfair, and some of the comments made about AJPP journals are erroneous. Specifically, the authors claim that only 1 AJPP journal has a stated policy on plagiarism. In fact 3 journals have specific stated policies in their guides for authors,(6-8) and all journals indicate they follow the policies of the International Committee of Medical Journal Editors, which identifies plagiarism as a form of scientific misconduct. When the authors correct their prevalence estimate they should also issue an additional correction for that inaccurate statement about the AJPP journal author guides.
Audits like Rohwers’ et al can be useful for journals considering how to improve their editorial processes and standards. The AJPP journals, with very limited resources, are working to improve their editorial practices and support for and education of authors, and the journal editors are looking for an affordable way to implement software to assess for similarity, duplication, and actual plagiarism as part of their workflows and plans for process improvement. It is unfortunate that the AJPP journals only recently received notification from the study authors with claims of serious plagiarism for 4 articles - at least 6 weeks after publication of the study and after media coverage of the misleading findings. We note that the communication from the study authors to a few AJPP journal editors includes a link to the COPE flowchart that defines clear plagiarism with the term “unattributed.” This further reinforces the problems with the published study and the need to correct the misleading estimate of the prevalence of actual plagiarism and the misrepresentation of AJPP journal policies.
Annette Flanagin, JAMA and the JAMA Network
David Ofori-Adjei, Ghana Medical Journal
Co-Directors, African Journal Partnership Program (AJPP), on behalf of AJPP Journal Editors
References
1. Rohwer A, Wager E, Young T, et al Plagiarism in research: a survey of African medical journals BMJ Open 2018;8:e024777. doi: 10.1136/bmjopen-2018-024777
Decline in neonatal mortality in Northern Ghana: Non-specific effects of BCG vaccination or Improvements in health systems?
In an ecological study carried out in Northern Ghana, Welaga et al., assessed changes in neonatal mortality rates (NMR) and BCG vaccination age from 2002 to 2012. The authors found that among home deliveries, median BCG vaccination age declined from 46 days in 1996 to 4 days in 2012. Within the same period , NMR decreased from 46 to 12 per 1000 live births (1). The authors concluded their study by suggesting that the significant decline in mortality observed may be due to the beneficial non-specific effects of early BCG vaccination. The authors should be commended for studying whether BCG vaccination may have non-specific effects. However, several issues need to be raised when interpreting these results.
1) Adjustment for other vaccine effects
The authors did not expand on the potential role that improvements on the Expanded Programme on Immunization (EPI) in Ghana may have played in reducing neonatal mortality. Diarrhea and Pneumonia are the main causes of neonatal mortality. Although still sub-optimal, Rotac and PCV3 immunization coverage estimates for Ghana in 2012 were significantly better than in 1996 or 2002 (2). A similar trend was observed for almost all the vaccines in the EPI schedule. For example, UNICEF immunization coverage estimates for Ghana indicate that DTP3 vaccine coverage increased from 71 % in 1996 to 92 %...
Decline in neonatal mortality in Northern Ghana: Non-specific effects of BCG vaccination or Improvements in health systems?
In an ecological study carried out in Northern Ghana, Welaga et al., assessed changes in neonatal mortality rates (NMR) and BCG vaccination age from 2002 to 2012. The authors found that among home deliveries, median BCG vaccination age declined from 46 days in 1996 to 4 days in 2012. Within the same period , NMR decreased from 46 to 12 per 1000 live births (1). The authors concluded their study by suggesting that the significant decline in mortality observed may be due to the beneficial non-specific effects of early BCG vaccination. The authors should be commended for studying whether BCG vaccination may have non-specific effects. However, several issues need to be raised when interpreting these results.
1) Adjustment for other vaccine effects
The authors did not expand on the potential role that improvements on the Expanded Programme on Immunization (EPI) in Ghana may have played in reducing neonatal mortality. Diarrhea and Pneumonia are the main causes of neonatal mortality. Although still sub-optimal, Rotac and PCV3 immunization coverage estimates for Ghana in 2012 were significantly better than in 1996 or 2002 (2). A similar trend was observed for almost all the vaccines in the EPI schedule. For example, UNICEF immunization coverage estimates for Ghana indicate that DTP3 vaccine coverage increased from 71 % in 1996 to 92 % in 2012 (2). These improved vaccination rates may therefore explain why the authors observed such a significant drop in mortality. Although the authors adjusted for year of vaccination, they did not provide any additional information on other vaccines nor did they provide information on which infections were associated with mortality in their study.
2) Heterogeneous effects on BCG and misclassification bias in the study
At the individual level, While BCG vaccination was protective against mortality among girls, the authors found no protective effect associated with BCG among boys ( HR=0.95 (0.20-4.25) (1). This was a surprising effect since BCG is known to reduce the risk of tuberculosis disease by about 50% (3). This suggests that either there was a misclassification of exposure in this study or there were other potential unmeasured confounders affecting these estimates. In addition, it is unclear why the authors did not provide a relative risk estimate comparing mortality among infants that were vaccinated early and those who were vaccinated a few weeks after birth. It seems unlikely that at the individual level, this estimate would be statistically or clinically significant.
3) The role of the neonatal immune system and delayed BCG-vaccination
Neonates’ innate and adaptive immune responses have been shown to improve over time and multiple BCG studies carried out in South African HIV-exposed and HIV-unexposed infants have shown that delaying BCG vaccination to a few weeks after birth leads to improved Th1 responses to BCG antigens but also other antigens such as Tetanus Toxoid(4,5,6). BGG has been shown to induce heterologous protection against unrelated pathogens via epigenetic reprogramming of monocytes (7). However, it is unclear, whether these non-specific effects are affected by the timing of vaccination as the authors seem to suggest in their conclusion (1)
Welaga et al. showed encouraging data indicating that neonatal mortality is significantly decreasing in Northern Ghana. The decline in the median BCG age suggests an overall improvement in health systems in and EPI coverage in Northern Ghana over the years. However, due to the nature of this study, it is difficult to assess the role of early BCG vaccination on neonatal mortality. This study highlights the need for Randomized controlled trials (RCTs) assessing the non-specific beneficial effects of BCG vaccination.
References
1) Welaga P, Debpuur C, Aaby P, Hodgson A, Azongo DK, Benn CS, Oduro AR. Is the decline in neonatal mortality in northern Ghana, 1996–2012, associated with the decline in the age of BCG vaccination? An ecological study. BMJ Open. 2018 Dec 1;8(12):e023752.
2) Ghana: WHO and UNICEF estimates of immunization coverage: 2017 revision accessed at: https://www.who.int/immunization/monitoring_surveillance/data/gha.pdf on December 20th 2018
3) Colditz GA, Brewer TF, Berkey CS, Wilson ME, Burdick E, Fineberg HV, Mosteller F. Efficacy of BCG vaccine in the prevention of tuberculosis: meta-analysis of the published literature. Jama. 1994 Mar 2;271(9):698-702.
4) Kagina BM, Abel B, Bowmaker M, Scriba TJ, Gelderbloem S, Smit E, Erasmus M, Nene N, Walzl G, Black G, Hussey GD. Delaying BCG vaccination from birth to 10 weeks of age may result in an enhanced memory CD4 T cell response. Vaccine. 2009 Sep 4;27(40):5488-95.
5) Tchakoute CT, Hesseling AC, Kidzeru EB, Gamieldien H, Passmore JA, Jones CE, Gray CM, Sodora DL, Jaspan HB. Delaying BCG vaccination until 8 weeks of age results in robust BCG-specific T-cell responses in HIV-exposed infants. The Journal of infectious diseases. 2014 Aug 8;211(3):338-46.
6) Blakney AK, Tchakoute CT, Hesseling AC, Kidzeru EB, Jones CE, Passmore JA, Sodora DL, Gray CM, Jaspan HB. Delayed BCG vaccination results in minimal alterations in T cell immunogenicity of acellular pertussis and tetanus immunizations in HIV-exposed infants. Vaccine. 2015 Sep 11;33(38):4782-9.
7) Kleinnijenhuis J, Quintin J, Preijers F, Joosten LA, Ifrim DC, Saeed S, Jacobs C, van Loenhout J, de Jong D, Stunnenberg HG, Xavier RJ. Bacille Calmette-Guerin induces NOD2-dependent nonspecific protection from reinfection via epigenetic reprogramming of monocytes. Proceedings of the National Academy of Sciences. 2012 Oct 23;109(43):17537-42.
My research has detected curious patterns of on/off switching in international deaths. Basically, deaths run at a baseline level and then suddenly switch-on to a new and higher level for around 12 to 18 months after which they switch-off and revert back to the baseline. They stay at baseline until the next switch-on event. Deaths in person's with Alzheimer's and other dementias seem highly sensitive to the switch-on events. This curious behaviour is most readily revealed using a rolling (running or moving) 12-month total or average.
In England, in-hospital deaths show the same on/off-switching.
Should you have access to monthly data it may be useful if you could apply such a rolling 12-month analysis of the data.
This is a note to indicate that BMJ Open is still looking into the disagreement between Albert Donnay and the authors of the paper.
We will post further updates on the article in due course.
We recently reported on brain tumour incidence time trends in 20 to 59 year old Australians, from 1982 to 2013, and analysed these in terms of mobile phone usage patterns and diagnostic improvements over that interval1. This was designed to determine whether claims that mobile phone use causes brain tumours, are consistent with the pattern of brain tumour incidence in Australia, and in particular to compare such incidence patterns with the results of the multinational Interphone case control study2. In summary, we reported that: 1/ Overall brain tumour incidence rates did not change over time; 2/ Increased glioblastoma incidence was seen during intervals that coincided with improvements in diagnostic technologies (CT, MRI); 3/ Decreased incidence of ‘unspecified’ tumours was seen during the same intervals; and 4/ No evidence of increased tumour incidence (including glioblastoma) related to mobile phone use was found (based on incidence rates seen during the period of substantial mobile phone use and on modelling using a range of hypothetical relative risks and latency periods).
Philips submitted a Letter to the Editor3 of BMJ Open, where he purports to show that there are ‘significant flaws and unjustifiable conclusions’ in the above paper. Although he may firmly hold this view, his letter does not provide any evidence of this, and we strongly disagree with his statement. We have addressed the substance of his letter below to hopefully obviate potential misunderstan...
Show MorePage 8/9; Acknowledgements.
The spelling of research assistant Rohan Navani was misspelt as Rohan Navari.
We have read with interest the article by Ball et al (2018) recently published in BMJ Open and note that they refer to our letter (Pereira Gray and Wilkie, 2017) which listed disadvantages of this system from the point of view of patients and where we reported the opposition of the National Association of Patient Participation (N.A.P.P.) to this system.
We agree with the authors that ‘telephone first’ system is a “fundamental” change in the provision of general practice.
The authors refer in detail to the independent review of this system Newbould et al (2017), which was published on the BMJ in 2017 and in which three of the authors were the same. We are puzzled by the way they summarise it.
Authors’ statements in 2018 can be contrasted with the published results in Newbould et al 2017. For example, Ball et al write “No evidence of reduced secondary care costs.” Whereas Newbould et al wrote “we found a significant increase of cost of admissions… leading to an estimated overall increase in secondary care costs of £11,766 per 10,000 patients (i.e. over £1 per patient registered in the general practices).
Secondly, Ball et al write “Little overall improvement in patient satisfaction as expressed in patient surveys” when Newbould et al reported:
1.GP communication composite-Significant fall (P<0.001)
2. Would you recommend your surgery?- Significant fall (P<0.001) 3.Seeing preferred GP- Significant fall (P<0.035)
Why h...
Show MoreThis is a useful study. May I suggest that the Output Area Classification (OAC) offers similar insights based on social groupings. Several studies have explored the use of the OAC relating to A&E attendance and Critical Care admission [1-3]. I suspect that your data is amenable to further helpful analysis using the OAC.
1. Beeknoo N, Jones R. Factors influencing A&E attendance, admissions and waiting times at two London hospitals. British Journal of Medicine and Medical Research 2016; 17(10): 1-29. doi : 10.9734/BJMMR/2016/28783
2. Beeknoo N, Jones R. Using Social Groups to Locate Areas with High Emergency Department Attendance, Subsequent Inpatient Admission and Need for Critical Care. British Journal of Medicine and Medical Research 2016; 18(6): 1-23. doi: 10.9734/BJMMR/2016/29208
3. Beeknoo N, Jones R. Using social groups to locate areas of high utilization of critical care. BBritish Journal of Healthcare Management 2016; 22(11): 551-560.
I worked on emergency ambulances in London from 1974 to 1978. I attended several bomb calls during the IRA campaign and it was terrifying to sit in a fibreglass ambulance knowing that there was a real risk of being right next to a car bomb that might be detonated with the intention of harming the emergency services. I was 19 at the time. Looking back, with my current knowledge, I can see that the experience was quite harmful for me. In addition to the existential threat there was also the fear of failing to perform and letting people down and being seen to be a coward. This also took its toll.
Other things also took a toll and they were not so obvious. Dealing with sick elderly patients was incredibly depressing. I came to fear growing old, because the only old people that I was meeting were ill and depressed and really not enjoying life. I saw so many old people living sad lives in grinding poverty.
Again, with maturity, this seems totally absurd, but as a 19 year old with no experience of healthy older people (my grandparents were all dead) ambulance work made me very sad. I was surrounded by other ambulance workers who I think tended to be able to cope by having sociopathic tendencies. A very toxic milieu!
My point here is that when I compared notes with ambulance workers with similar seniority in more rural settings and away from the IRA bombs, their experiences were entirely different. They attended the occasional serious RTC, but mos...
Show MoreKaripidis et al report that in Australia, glioblastoma (GBM) incidence increased significantly only during the period 1993-2002. They conclude that this was due to diagnostic improvements and that there has been no increase in any brain tumour histological type or glioma location that can be attributed to mobile phones.
I am lead author of an ecological study published early in 2018 that examined detailed underlying incidence trends for 81,835 biologically malignant (ICD10 C70) brain tumours, recorded in England over the period 1995-2015 [1]. Karipidis et al cite our study and note that we reported that the overall incidence of GBM more than doubled over that time period (from 2.4 to 5.0 per 100,000 person years, age-standardised to the European Standard Population ESP2013, with annual case numbers rising from 983 to 2531). Zada et al (2012) [2] and Ho et al (2014) [3] have reported similar trends.
Although we briefly discussed five possible causal factors that might have contributed to the rise in incidence, we stated that our article reported incidence data trends and did not provide additional evidence for the role of any particular risk factor. We showed that most of the rise in incidence was in people over 55 years of age. We discussed the possible mix of promotion of lower grade tumours and de-novo tumours. We also discussed the effect of better imaging and more accurate diagnosis and concluded that although it did have an effect, especially for topogra...
Show MoreWe write to express our concern about the prevalence estimate of plagiarism in African medical journals in the study reported by Rohwer et al.(1) The authors’ finding that 63% of African medical journal articles are plagiarized to some degree is a gross overestimate.
The study definitions of “some,” “moderate,” and “extensive” plagiarism are unvalidated and, as the authors admit in the fourth paragraph of their Discussion section, lack inter-rater reliability and precision. Articles were classified as having “some” plagiarism if there were as few as 1-2 sentences that included identical words or sentences in another article by different authors even if the sentences were properly referenced. Numerous publishing organizations, including the Council of Science Editors,(2) the World Association of Medical Editors,(3) and the US Office of Research Integrity,(4) reserve the use of plagiarism for instances when another’s words are used without proper credit or attribution. The authors developed their definition based on suggestions from the Committee on Publication Ethics (COPE), yet even COPE’s Flowchart for managing suspected plagiarism in a submitted manuscript defines plagiarism as “unattributed use of large portions of text and/or data.”(5)
In fairness to the African journals implicated in the study, we request the authors go back to their data, identify all instances in which identical wording with formal source citations were defined as plagiarism, recalcu...
Show MoreDecline in neonatal mortality in Northern Ghana: Non-specific effects of BCG vaccination or Improvements in health systems?
In an ecological study carried out in Northern Ghana, Welaga et al., assessed changes in neonatal mortality rates (NMR) and BCG vaccination age from 2002 to 2012. The authors found that among home deliveries, median BCG vaccination age declined from 46 days in 1996 to 4 days in 2012. Within the same period , NMR decreased from 46 to 12 per 1000 live births (1). The authors concluded their study by suggesting that the significant decline in mortality observed may be due to the beneficial non-specific effects of early BCG vaccination. The authors should be commended for studying whether BCG vaccination may have non-specific effects. However, several issues need to be raised when interpreting these results.
Show More1) Adjustment for other vaccine effects
The authors did not expand on the potential role that improvements on the Expanded Programme on Immunization (EPI) in Ghana may have played in reducing neonatal mortality. Diarrhea and Pneumonia are the main causes of neonatal mortality. Although still sub-optimal, Rotac and PCV3 immunization coverage estimates for Ghana in 2012 were significantly better than in 1996 or 2002 (2). A similar trend was observed for almost all the vaccines in the EPI schedule. For example, UNICEF immunization coverage estimates for Ghana indicate that DTP3 vaccine coverage increased from 71 % in 1996 to 92 %...
Dear Sirs,
My research has detected curious patterns of on/off switching in international deaths. Basically, deaths run at a baseline level and then suddenly switch-on to a new and higher level for around 12 to 18 months after which they switch-off and revert back to the baseline. They stay at baseline until the next switch-on event. Deaths in person's with Alzheimer's and other dementias seem highly sensitive to the switch-on events. This curious behaviour is most readily revealed using a rolling (running or moving) 12-month total or average.
In England, in-hospital deaths show the same on/off-switching.
Should you have access to monthly data it may be useful if you could apply such a rolling 12-month analysis of the data.
You can access a list of publications relating to this research at http://www.hcaf.biz/2010/Publications_Full.pdf
I have proposed that this behaviour may reflect some new type or kind of disease outbreak, however, this is open to further research.
I hope this response is helpful.
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