published between 2015 and 2018
As an African American female physician and practice owner with a 37 year professional history I fully concur with the findings of this article. I have commented on other writings on Doximity around the issues of professional attire and efforts to restrict wearing white coats. As a practice owner with locations in San Francisco and Sacramento I travel weekly by Amtrak and this experiences reinforces my opinion that professional attire for a physician can improve patient and public interactions. In the course of my career I have experienced numerous incidents in which I was demeaned, harassed or disrespected as a physician because of my race and gender in areas dominated traditionally by white males. I have authored numerous writings about my experience as the first African American female to train in neurological surgery in the University of California system and my experiences as a flight physician and post doctoral fellow for Stanford Life Flight. I have been mistaken for a custodian, a "girl" and on a good day a pediatrician in my years of training. My white coat and my professional attire make all the difference in the world in how patients relate to me. When I appear without it I am called Miss or Ms. When I have it on I am called Doctor.I will never give up wearing my white coat!
To the Editor:
We read the recent articles from Kim et al. with great interest and appreciate the authors’ efforts to evaluate the suitability of the two models regarding the prediction of incidentally-detected pulmonary subsolid nodules (SSNs), as well as their reports that there were substantial differences. However, we would like to highlight two concerns that we have regarding their study.
First, there is a lack of description regarding whether an adequate pathological diagnosis was performed. We would like to know who performed the diagnosis and how it was made. In predictive model research, it is preferable that outcomes are evaluated with masked predictors, as there might be bias in estimating associations between predictors and outcomes. 
Secondly, there might have been a sampling bias before surgery selection. Among patients with SSNs, surgery might be preferentially performed, especially for patients who show a high possibility of lung cancer. Further, additional upper lobes and peripheral nodules, which were difficult to diagnose by bronchoscopy examination, might be selected and resected. Thus, cases of atypical adenomatous hyperplasia (AAH)/ adenocarcinoma in situ (AIS) might comprise a smaller portion of the study cohort, and minimally invasive adenocarcinoma (MIA)/ invasive pulmonary adenocarcinoma (IPA) might be diagnosed more frequently. Clinically, we often struggle to decide whether the nodule is malignant in a case where surgery c...
Secondly, there might have been a sampling bias before surgery selection. Among patients with SSNs, surgery might be preferentially performed, especially for patients who show a high possibility of lung cancer. Further, additional upper lobes and peripheral nodules, which were difficult to diagnose by bronchoscopy examination, might be selected and resected. Thus, cases of atypical adenomatous hyperplasia (AAH)/ adenocarcinoma in situ (AIS) might comprise a smaller portion of the study cohort, and minimally invasive adenocarcinoma (MIA)/ invasive pulmonary adenocarcinoma (IPA) might be diagnosed more frequently. Clinically, we often struggle to decide whether the nodule is malignant in a case where surgery cannot be performed because of age, lung capacity, or social background. We urge Kim et al. to reanalyze and include patients who were diagnosed by non-surgical means, such as bronchoscopy.
 Moons KGM, Altman DG, Reitsma JB, et al. “Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD): Explanation and Elaboration. Ann Intern Med. , p. 162:W1–73., 2015.
Please note, due to a production error, reference 40 appears incorrectly in the manuscript. It should read:
Wright, L.M, & Leahey, M. Nurses and Families: A guide to family assessment and intervention. 6th ed. Philadelphia: FA Davis, 2013.
The statement that our cited study  demonstrated an issue of declined patient adherence over time is not entirely accurate. By contrast, our HeartCycle study demonstrated excellent adherence to performing daily tasks of weighing and measuring blood pressure, 90% of the patients were still adherent to these tasks at 6 months and adherence remained stable over time. We recognise however patients were less compliant with completing daily symptom questionnaires long term. There is a behavioural dichotomy therefore between carrying out a daily monitoring task (such as stepping on a weighing scale) and reporting symptoms via questionnaire. Arguably patients perceived the importance of daily weighing, and blood pressure monitoring to be greater than the daily reporting of symptoms such as breathlessness, that they may or may not be experiencing. We look forward to learning of the outcomes of the ITEC-CHF trial.
. Stut W, Deighan C, Cleland JG, et al. Patient adherence to self-care behaviour in the HeartCycle study. Patient Prefer Adherence 2015;9: 1195-206.
Recently, the work “Urban-rural differences in factors associated with willingness to receive eldercare among the elderly: a cross-sectional survey in China” was published in BMJ Open, it discussed the influencing factors of the eldercare model, and I had the pleasure to enjoy it. But I have a question that in the ninth paragraph in introduction section: “Many other recent studies have examined differences in willingness to receive eldercare between urban and rural areas.” But, there is not a reference, indicating the “many”? Biomedical research waste [2,3] is heatedly discussed recently, and “Towards evidence based research”  was published in BMJ and it pointed out that all new research should be based on existing evidence. So, should there be a relevant reference?
1. Xing YN, Pei RJ, Qu J, et al. Urban-rural differences in factors associated with willingness to receive eldercare among the elderly: a cross-sectional survey in China[J]. BMJ Open 2018;8:e020225.
2. Chalmers I, Glasziou P. Avoidable waste in the production and reporting of research evidence[J]. Lancet, 2009, 374(9692):86-89.
3. Moher D, Glasziou P, Chalmers I, et al. Increasing value and reducing waste in biomedical research: who's listening?[J]. Lancet, 2015, 387(10027):1573-1586.
4. Lund H, Brunnhuber K, Juhl C, et al. Towards evidence based research[J]. Bmj, 2016, 355(1):i5440.
We agree that variation exists across UK medical schools as highlighted by the cited paper by McManus et al. (2008). It was partly this that we had in mind when we state, in the limitation section of our discussion:
“In terms of the outcome measures, the categorisation of undergraduate examinations into skills and knowledge was not operationalised and therefore rely on the participating medical schools to categorise the evaluations. Thus, their definition may vary across medical schools. While some of this variation was handled by the use of multilevel modelling, a more robust definition of undergraduate ‘skills’-based assessments may have been helpful in predicting clinically orientated performance, which may have been a more faithful proxy for later medical practice. In this regard, a methodology has been proposed to achieve this through the ‘nationalisation’ of ‘local’ measures of undergraduate medical school performance for fair comparisons of graduating medical doctors.” [page 10, paragraph 3].
Indeed, we recognise the use of ‘local educational measures’ as a particular challenge in UK-based Medical Education Research and are shortly to evaluate whether our approach to adjusting for this using ‘Peer Competition Rescaling’ (applied in the report by Tiffin & Paton, 2017) is valid in these circumstances. Thus, it is true to state that at present we cannot rule out the potential selection effect that Dr Banerjee highlights as a possibility. Only emerging...
Indeed, we recognise the use of ‘local educational measures’ as a particular challenge in UK-based Medical Education Research and are shortly to evaluate whether our approach to adjusting for this using ‘Peer Competition Rescaling’ (applied in the report by Tiffin & Paton, 2017) is valid in these circumstances. Thus, it is true to state that at present we cannot rule out the potential selection effect that Dr Banerjee highlights as a possibility. Only emerging evidence that performance on national performance measures, or where valid corrections can be applied, can support or refute this potential mechanism as a (contributory) cause of our observed results.
Nevertheless, we would wish to highlight that there is also a pragmatic issue to consider; that whatever variation in academic standards exists across UK medical schools, those who successfully graduate join the medical workforce. Therefore, unless those with lower A-level grades from less well performing secondary schools are eventually shown to have inferior patient outcomes in terms of clinical practice, any differences on national academic measures may be just that: academic.
Tiffin PA, Paton LW. Exploring the validity of the 2013 UKCAT SJT prediction of undergraduate performance in the first year of medical school: summary version of report. 2017 https://www.ukcat.ac.uk/ media/1119/exploring-the-validity-of-the-2013-ukcat-sjt-predictionof-ug-performance-in-1st-yr-of-med-school-summary-versionposted-27032017.pdf (accessed 19 Sep 2017).
We read with great interest the comprehensive review of primary care consultation duration in 67 countries between 1946 and 2016 by Irving et al (1). This review is especially timely given rising physician burnout, as well as dissatisfaction among both doctors and patients in the U.S. As the authors note, many physicians are frustrated by the limited time available to interact with patients.
The increasing time of U.S. physicians with patients surprised us. Primary care physicians in the U.S. rank fifth out of ten high-income countries on dissatisfaction with time spent per patient (2). What explains this apparent mismatch of quantitative trends and satisfaction?
One candidate explanation is that much of physician time is spent on activities other than communication with patients. According to an observational study in 2015 of 57 ambulatory care physicians (primary care, cardiology, and orthopedics) in 16 practices in 4 states, of time spent with patients in the exam room, 53% was spent face-to-face, 37% on the electronic health record (EHR) and desk work, and 9% on administrative tasks (3).
Thus, we wondered if the U.S. trend in primary care consultation duration reported by Irving et al aligned with historical trends in EHR uptake. In the Figure [https://blogs.bmj.com/bmjopen/files/2018/06/Figure-One-2.jpg ] we compare these two temporal patterns. Examination of the Irving da...
Thus, we wondered if the U.S. trend in primary care consultation duration reported by Irving et al aligned with historical trends in EHR uptake. In the Figure [https://blogs.bmj.com/bmjopen/files/2018/06/Figure-One-2.jpg ] we compare these two temporal patterns. Examination of the Irving data suggest to us two time periods with different slopes: nearly flat from 1992-2004, and then rising from 2004-2012. The rising period aligns well in time with rising EHR uptake (4). Although comparison of these two trends is only suggestive, we believe it provides strong cautionary evidence against interpreting the rise in consultation duration as a rise in physician-patient communication.
Physicians do not view the increasing EHR burden favorably. The ambulatory care study noted above found that physician satisfaction results from providing high quality medical care and caring for patients, while EHR/desk work and the complexity of reimbursement and administrative tasks contribute to dissatisfaction (5). Physician satisfaction with the EHR is far lower in the U.S. (52%) than in eight other wealthy nations (64% to 86%) (2).
While these issues are beyond the scope of Irving et al’s review, we believe that attention must be focused on primary care consultation duration that entails undisturbed communication with the patient, absent attending to the computer. This time is central to caring for patients and its continual undermining is a risk to the health of both patients and physicians.
1. Irving G, Neves AL, Dambha-Miller H, et al. International variations in primary care physician consultation time: a systematic review of 67 countries. BMJ Open. 2017; 7(10):e017902. doi:10.1136/bmjopen-2017-017902.
2. Osborn R, Moulds D, Schneider EC, Doty MM, Squires D, Sarnak DO. Primary Care Physicians In Ten Countries Report Challenges Caring For Patients With Complex Health Needs. Health Aff (Millwood). 2015 Dec;34(12):2104-12. doi: 10.1377/hlthaff.2015.1018.
3. Sinsky C, Colligan L, Li L, et al. Allocation of Physician Time in Ambulatory Practice: A Time and Motion Study in 4 Specialties. Ann Intern Med 2016;165(11):753-760.
4. Hsiao C-J, Hing E, Ashman J. Trends in Electronic Health Record System Use Among Office-based Physicians: United States, 2007–2012. National Health Statistics Reports, No. 75, May 2014.
5. Colligan L, Sinsky C, Goeders L, Schmidt-Bowman M, Tutty M. Sources of physician satisfaction and dissatisfaction and review of administrative tasks in ambulatory practice: A qualitative analysis of physician and staff interviews. October 2016. Available at: ama-assn.org/go/psps.
In view of the high mortality and the need for early diagnosis of melanoma, Harrington et al.(1) reviewed the studies on the diagnostic rules to stratify patients with suspected melanoma and concluded that the ABCD rule is more useful than the 7-point checklist. Despite the importance of this result, future evaluations of diagnostic methods should also include among the comparisons the diagnostic tools assisted by artificial intelligence. Computational analysis of dermatological images has shown great potential as a diagnostic tool for melanoma (2,3), and can contribute to reduce costs, increase access and the scope of the examination to regions without specialists, allowing early diagnosis by primary care physicians, mainly in remote areas, lacking specialists.
1. Harrington, E., Clyne, B., Wesseling, N., Sandhu, H., Armstrong, L., Bennett, H., & Fahey, T. (2017). Diagnosing malignant melanoma in ambulatory care: a systematic review of clinical prediction rules. BMJ Open, 7(3), e014096. http://doi.org/10.1136/bmjopen-2016-014096
2. Safran T, Viezel-Mathieu A, Corban J, Kanevsky A, Thibaudeau S, Kanevsky J. Machine learning and melanoma: The future of screening. J Am Acad Dermatol. 2018 Mar;78(3):620-621. doi: 10.1016/j.jaad.2017.09.055. Epub 2017 Oct 6. PubMed PMID: 28989109.
3. Jaworek-Korjakowska J, Kłeczek P. Automatic Classification of Specific Melanocytic Lesions Using Artificial Int...
3. Jaworek-Korjakowska J, Kłeczek P. Automatic Classification of Specific Melanocytic Lesions Using Artificial Intelligence. Biomed Res Int.
2016;2016:8934242. doi: 10.1155/2016/8934242. Epub 2016 Jan 17. PubMed PMID: 26885520; PubMed Central PMCID: PMC4739011.
We have with great interest read the article by Hansen et al. (1). We have though two comments for reflection. First, the authors state that the stable incidence of cervical cancer indicates “apparent exhaustion of the cancer-reducing potential of current cervical screening”. Given that the coverage by examination can be increased with e.g. self-sampling (2), that the follow-up of abnormal findings is still suboptimal (3), and that Norway among other countries plans implementation of HPV-based screening (4) which provides better protection than cytology-based screening (5), we find the authors’ statement to be a bit too pessimistic especially for the many birth cohorts of women who still have to rely on screening for their primary protection against cervical cancer.
Second, the authors divide the HPV-vaccine preventable cancers into cervical squamous cell carcinomas and other cancers, and they argue - based on increasing trends - that the HPV vaccine can prevent a “substantial” number of these other cancers in both women and men. It should, however, be taken into account that the incidence of these cancers is low despite increasing trends. Out of 32,000 new cancer cases in Norway in 2016 (6), 271, 0.8%, fell into the other HPV-vaccine preventable category. The additional potential for prevention of cervical cancer is actually greater. With 3205 treatments per year for cervical intraepithelial neoplasia (3), the HPV-vaccine could prevent an addi...
Second, the authors divide the HPV-vaccine preventable cancers into cervical squamous cell carcinomas and other cancers, and they argue - based on increasing trends - that the HPV vaccine can prevent a “substantial” number of these other cancers in both women and men. It should, however, be taken into account that the incidence of these cancers is low despite increasing trends. Out of 32,000 new cancer cases in Norway in 2016 (6), 271, 0.8%, fell into the other HPV-vaccine preventable category. The additional potential for prevention of cervical cancer is actually greater. With 3205 treatments per year for cervical intraepithelial neoplasia (3), the HPV-vaccine could prevent an additional 400-500 cases of cervical cancer per year (7). Therefore, the HPV vaccine’s prevention potential is still most relevant for the women’s risk of cervical cancer (8).
Malene Skorstengaard University of Copenhagen
Lise Thamsborg Denmark
Elsebeth Lynge 31 May 2018
1. Hansen BT, Campbell S, Nygård M. Long-term incidence trends of HPV-related cancers, and cases preventable by HPV vaccination: a registry-based study in Norway. BMJ Open. 2018;8(2):e019005.
2. Enerly E, Bonde J, Schee K, Pedersen H, Lönnberg S, Nygård M. Self-sampling for human papillomavirus testing among non-attenders increases attendance to the norwegian cervical cancer screening programme. PLoS One. 2016;11(4):1–14.
3. Norwegian Cancer Registry. Annual report 2015, Cervical screening. Oslo, 2016 [In Norwegian].
4. Kreftregisteret. https://www.kreftregisteret.no/Registrene/Kreftstatistikk/. Cancer in Norway 2016 tables.
5. Ronco G, Dillner J, Elfström KM, Tunesi S, Snijders PJF, Arbyn M, et al. Efficacy of HPV-based screening for prevention of invasive cervical cancer: Follow-up of four European randomised controlled trials. Lancet. 2014;383(9916):524–32.
6. Larsen IK, Møller B, Johannesen TB, Larønningen S, Robsahm TE, Grimsrud TK et al. Cancer in Norway 2016. Oslo, 2017;103.
7. Barken SS, Rebolj M, Andersen ES, Lynge E. Frequency of cervical intraepithelial neoplasia treatment in a well-screened population. Int J Cancer. 2012;130(10):2438–44.
8. Skorstengaard M, Thamsborg LH, Lynge E. Burden of HPV-caused cancers in Denmark and the potential effect of HPV-vaccination. Vaccine. 2017;35(43):5939–45.
In the original publication a consensus document on providing access to individual participant data (IPD) from clinical trials was developed, using a broad interdisciplinary approach within the H2020 funded project CORBEL. The taskforce reached consensus on 10 principles and 50 recommendations, representing the fundamental requirements of any framework used for the sharing of clinical trials data. What was still missing was a generic framework or architecture for data sharing that could be used for modelling, describing, and designing operations, data requirements, IT-systems and technological solutions. As a first step in developing an inventory of existing tools/services, and examining their quality and applicability for data sharing, a systematic analysis of processes and actors involved in data sharing was performed, based on the consensus document and summarized in a follow-up paper (1). The work done resulted in a systematic and comprehensive list of the processes and subprocesses that need to be supported to make data sharing a reality in the future. It is foundational work against which existing tools/services can be mapped, and gaps, where new tools/services are needed, can be identified. This follow-up work will facilitate the extension of the ideas in the original paper to create a generic but practical framework for the sharing of IPD from clinical trials. That framework is currently under development.
1. Ohmann C, Canham S, Banzi R e...
1. Ohmann C, Canham S, Banzi R et al. Classification of processes involved in sharing individual participant data from clinical trials, F1000Research 2018, 7:138