|Year : 2020 | Volume
| Issue : 6 | Page : 191-193
Combined case record forms for collating obstetric outcomes in rare rheumatic diseases
Rajat Kharbanda, R Naveen, Durga Prasanna Misra, Vikas Agarwal, Latika Gupta
Department of Clinical Immunology and Rheumatology, Sanjay Gandhi Post Graduate Institute of Medical Sciences, Lucknow, Uttar Pradesh, India
|Date of Submission||22-Apr-2020|
|Date of Acceptance||20-May-2020|
|Date of Web Publication||18-Jan-2021|
Dr. Latika Gupta
Department of Clinical Immunology and Rheumatology, Sanjay Gandhi Post Graduate Institute of Medical Sciences, Lucknow - 226 014, Uttar Pradesh
Source of Support: None, Conflict of Interest: None
Background: Evaluating the fertility and obstetric outcomes in women with rare rheumatic diseases is challenging as it needs to take into account various influencing factors.
Aims and Objectives: The aim is to draft a structured case record form (CRF) for collating obstetric outcomes in rheumatic diseases
Materials and Methods: Clinical CRFs were designed for inflammatory myositis, ANCA associated vasculitis, Takayasu arteritis and systemic sclerosis with the objectives in mind, taking into account disease characteristics, drugs administered, and the changes related to the pregnant state. The forms underwent four rounds of revision by two rheumatologists with trial runs on three patients each. The form was scrutinized for face validity, ambiguity and were designed to ease filling them in a busy outpatient setup.
Results: The CRF forms for obstetric outcomes in patients were labelled as version 10.0, 11.0, 12.0, and 13.0 for myositis, AAV, TA, and SSc.
Conclusion: Beginning with a well-designed CRF is the first step in collating proper data for research. This paper details the steps involved in the same for collating obstetric outcomes in tfour rare rheumatic illnesses.
Keywords: Case record form, myositis, obstetric outcomes, rheumatic diseases
|How to cite this article:|
Kharbanda R, Naveen R, Misra DP, Agarwal V, Gupta L. Combined case record forms for collating obstetric outcomes in rare rheumatic diseases. Indian J Rheumatol 2020;15:191-3
| Introduction|| |
Rheumatic diseases (RDs) affect women with childbearing potential, often bringing the rheumatologists to the cross-roads of the disease and conception. Although in older times women with complicating RDs were advised against pregnancy, the current advances in therapy have paved the way for earlier diagnosis, better disease control, and higher quality of life, which brings in greater consideration of bearing a child among women with RDs. Thus, understanding the effect of pregnancy on RDs, and vice versa, is vital to a good preconception counseling, which delivers focused care to high-risk individuals.
In addition, there is a paucity of data on the pregnancy outcome of Indian patients with RDs. There is a huge gap in the knowledge and practice of contraception use by patients with rheumatological disorders. Illiteracy and sociocultural factors add further layers to the challenge of managing a pregnancy. The rare occurrence of certain RDs makes data collection pertaining to pregnancies challenging. Thus, collaborative efforts are the key where population-based studies are not feasible due to lack of a structured referral system.
The number of researchers with a dedicated interest, and an appropriate placement to carry out structured research in a rare disease, is limited. The Predictors of Pregnancy Outcome: Biomarkers in Antiphospholipid Antibody Syndrome and Systemic Lupus Erythematosus (PROMISSE) study, took longer to recruit due to lack of a unified data set across registries. Thus, providing various collaborators with a structured case record form (CRF) is the first step in a time-efficient research model for sustainable research. The recent increase in multicentric research in this area demonstrates the commitment of the community to collaborative group- based approach.
The COLLECT, a new multinational collaborative database for pregnancy research funded by the Bill and Melinda Gates Foundation is one such initiative, wherein a series of standard pages record patient demographics and baseline characteristics, followed by standard pregnancy outcome measures, with optional addition of supplementary modules to suit additional studies. The facilities for translation and the option of converting the existing databases to the COLLECT format at a modest cost add impetus to the initiative. A proper CRF should have common data elements which are internationally recognized standard terms of reporting diseases. This would ensure uniformity of the data entered.
The need for adequately powered studies to draw meaningful conclusions from the data collected cannot be overemphasized. The heterogeneity of various studies limits the interpretability of data from collated studies as in various meta-analysis. Thus, comprehensive CRFs can overcome this shortfall by building on preexistent peer-reviewed CRFs. Only then can the various types of rare diseases be stratified for various levels of complexity and appropriate management algorithms be devised. We describe herein a follow-up CRF to the same effort.
| Methods|| |
The CRF for structured data collection on obstetric outcomes in RDs was first devised in June 2016 with an aim to gather information on the effect of disease on pregnancy and vice versa, and address issues regarding contraception and marital status when influenced by the occurrence of the disease. Because the emotional aspects of the disease such as fear, depression, and social withdrawal are the domains of psychologists and need a trained assessor, these were excluded. The form was first devised for patients with inflammatory myositis (IIM), and subsequently for ANCA-associated vasculitis (AAV), Takayasu's arteritis (TA), and later for systemic sclerosis (Ssc) [Table 1], Supplementary [Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6], [Table 7].[Additional file 1]
The objective is to get information of all aspects beginning from menstrual history, issues related to marriage, contraception, and conceptions. The forms underwent four rounds of modifications over 2 weeks, done by two rheumatologists who reviewed this subsequent to testing on three patients in every round. The form was further scrutinized for ambiguity and repetitions. A consensus on the final forms for IIM, AAV, and TA was reached on June 2017. The form for SSc was designed in December 2019 and a consensus was reached by a similar process in February 2020 [Figure 1].
|Figure 1: Methodology of framing a case record form for obstetric outcomes in rheumatic diseases|
Click here to view
Highlights of the form include an intensive data collection, making it convenient to enter and hence time efficient in a busy outpatient setting. A glossary explaining the various items in the CRF was also devised for the users. To ensure patient confidentiality in collaborative efforts, the patient names in the CRF were made optional.
The current clinical status and the activity and damage of the diseases were quantified using the standard outcome measures as previously described.,,, For diseases where the nature of the disease (eg., SSc) might preclude the use of standard outcome measures, (e.g., Ssc), a physician estimate of disease activity was also added. Data on baseline features such as clinical diagnosis, demographics, baseline clinical characteristics, and investigations such as autoantibody results and biopsy findings were added as supplementary data to be included when available. The average CRF filling time was 15 min.
Standard guidelines for CRF designing were followed. The patient codes were added in the CRF to offer understanding of center and the assessor. The form was further scrutinized for language and face validity. Ambiguity was removed and duplicates were eliminated. Wherever feasible, checkboxes were preferred over circling the most appropriate answer. For investigations, the option “Not done” was moved above the other options, wherever considered sensible, and redundant bits were removed. Highlights of the form include coverage of all aspects of the disease and pregnancy and data collection with predetermined options which can be checked, making it convenient to enter and hence time efficient in a busy outpatient setting. A glossary explaining the various items in the CRF was also devised for the users. Columns were added to enable capturing clinical details of more than one pregnancy, wherever applicable. The CRF forms for obstetric outcomes in patients were labeled as version 10.0, 11.0, 12.0, and 13.0 for myositis, AAV, TA, and SSc, respectively, so that revised versions (developed as and when the need be, in line with the requirements of future projects) can be identified by the number after the decimals (e.g., 4.1, or 5.1).
| Discussion|| |
A comprehensive management of these multisystemic diseases is ideal, for which a systematic assessment at every follow-up is of utmost importance. Further, such collections of information over time can be of immense help in understanding the course of these rare diseases. A recent review of the European Network of Pregnancy Registers in Rheumatology (EuNeP) found that similar variables collected differed considerably among the various collaborating registers, making data collation challenging. The EULAR also recently recommended a structured data set for uniformity in collative research.
It is increasingly being recognized that CRF is the key step in ensuring a well-planned study. Drafting a case report form requires meticulous planning. A CRF must address the study hypothesis clearly, and at the same time be user friendly, accurate, scientific, and valid. Duplication and redundancy should be avoided. Cluttering of excessive data on a single sheet should be avoided.
The best way to devise a valid CRF is to subject the draft version to numerous rounds of corrections after identifying errors by filling them for paper cases. The average time taken to fill a CRF should be no more than half an hour as time is of essence in a busy outpatient clinic. It is ideal to have a header conveying the protocol identification (ID), site code, subject ID, and patient initials or indirect identifiers. Similarly, a footer can include the investigator signature, date of signature, version number, and page number. A poorly designed CRF leads to questionable validity of the study. A clear glossary explaining each entry is a must for a dedicated CRF to ensure uniformity of filling across multicenters.
This CRF was designed for ease of filling in, with built-in edit checks tagged to each data field, with an added advantage of utilizing a scanning system which can integrate into a software for auto-recording of data for digital archiving in cloud-based servers, thus eliminating human errors due to manual entries. Similar methods have been employed for large multicentric studies such as the DCVAS study.
Patients with rheumatic diseases can present to different specialists depending on the first organ system involved (cardiologist for TA, nephrologist for vasculitis, neurologist for myositis, and dermatologist for Ssc). Such structured data collection can provide the opportunity of cross-discipline collaboration to expand our perspective of the disease, which is of even greater relevance in times of big data and artificial intelligence. A similar collaboration has recently been formed to study the outcomes of pregnancy in women with chronic kidney disease.
Thus, the importance of unified data sets cannot be overemphasized. While recent publications are pointers to such efforts toward mining data from various registries, preexistent curated CRFs can save effort in prospective studies as well. The availability of such CRFs in the public domain may enable time-efficient continued data accrual longitudinally across geographic and decadal boundaries. Bureaucratic challenge for sharing data and biologic samples across institutions is a challenge experienced by every researcher across the globe, though the availability of a designed CRF can obviate some effort in this direction.
Collaborative studies on rare rheumatic diseases calls for proper date collection and collation. This requires structured case report form which is accurate and easy to use. This paper is the first step involved in collating data on obstetric outcomes in the four rare rheumatic diseases.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Mohan MC, Ravindran V. Lupus pregnancies: An Indian perspective. Indian J Rheumatol 2016;11 Suppl S2:135-8.
Clancy CM, Margolis PA, Miller M. Collaborative networks for both improvement and research. Pediatrics 2013;131 Suppl 4:S210-4.
Mellins E, Rider L. Clinical research networks: A step towards evidence-based practice in pediatric rheumatology. Nat Rev Rheumatol 2007;3:59.
Salmon JE. PROMISSE: Progress in understanding pregnancy complications in patients with SLE. Arthritis Res Ther 2012;14 Suppl 3:A39.
Corrao G, Rea F, Ghirardi A, Soranna D, Merlino L, Mancia G. Adherence with antihypertensive drug therapy and the risk of heart failure in clinical practice. Hypertension 2015;66:742-9.
Myers JE, Myatt L, Roberts JM, Redman C; Global Pregnancy Collaboration (CoLab). COLLECT, a collaborative database for pregnancy and placental research studies worldwide. BJOG 2019;126:8-10.
Roberts JM, Mascalzoni D, Ness RB, Poston L. Collaboration to understand complex diseases preeclampsia and adverse pregnancy outcomes. Hypertension 2016;67:681-7.
Rider LG, Aggarwal R, Machado PM, Hogrel JY, Reed AM, Christopher-Stine L, et al
. Update on outcome assessment in myositis. Nat Rev Rheumatol 2018;14:303-18.
Suppiah R, Robson J, Luqmani R. Outcome measures in ANCA- associated vasculitis. Rheum Dis Clin North Am 2010;36:587-607.
Merkel PA, Silliman NP, Clements PJ, Denton CP, Furst DE, Mayes MD, et al
. Patterns and predictors of change in outcome measures in clinical trials in scleroderma: An individual patient meta-analysis of 629 subjects with diffuse cutaneous systemic sclerosis. Arthritis Rheum 2012;64:3420-9.
Aydin SZ, Merkel PA, Direskeneli H. Outcome measures for Takayasu's arteritis. Curr Opin Rheumatol 2015;27:32-7.
Lu Z, Su J. Clinical data management: Current status, challenges, and future directions from industry perspectives. Open Access J Clin Trials 2010;2:93-105.
Meissner Y, Strangfeld A, Costedoat-Chalumeau N, Förger F, Goll D, Molto A, et al
. European Network of Pregnancy Registers in Rheumatology (EuNeP) – An overview of procedures and data collection. Arthritis Res Ther 2019;21:241.
Radner H, Chatzidionysiou K, Nikiphorou E, Gossec L, Hyrich KL, Zabalan C, et al.
2017 EULAR recommendations for a core data set to support observational research and clinical care in rheumatoid arthritis. Ann Rheumat Dis 2018;77:476-9.
Bellary S, Krishnankutty B, Latha MS. Basics of case report form designing in clinical research. Perspect Clin Res 2014;5:159-66.
] [Full text]
Craven A, Robson J, Ponte C, Grayson PC, Suppiah R, Judge A, et al
. ACR/EULAR-endorsed study to develop Diagnostic and Classification Criteria for Vasculitis (DCVAS). Clin Exp Nephrol 2013;17:619-21.
Alarcón-Riquelme ME. Big data: The opportunity to think outside the discipline. Nat Rev Rheumatol 2019;15:639-40.
Ashuntantang GE, Garovic, VD, Heilberg, IP, Lightstone L. Kidneys and women's health: Key challenges and considerations. Nature Reviews Nephrology 2018;4:203-10. doi:10.1038/nrneph.2017.188.
Chatzidionysiou K, Hetland ML, Frisell T, Di Giuseppe D, Hellgren K, Glintborg B, et al
. Opportunities and challenges for real-world studies on chronic inflammatory joint diseases through data enrichment and collaboration between national registers: The Nordic example. RMD Open 2018;4:e000655