Advancing Research in Resource-Limited Settings: Good Research Starts With Good Training in Evidence-Based Medicine

Advancing Research in Resource-Limited Settings: Good Research Starts With Good Training in Evidence-Based Medicine

International Perspectives

May 19, 2022

Dr. Khalid El Bairi headshotBy Khalid El Bairi, MD

Read Part 1 and Part 2.

Performing research that does not involve patient data, such as narrative and critical reviews on emerging topics in gynecologic oncology with a focus on ovarian cancer, was my first attempt to have an exhaustive understanding of my new research topic—improving ovarian cancer research in Morocco. I knew earlier during my career at medical school that conducting literature reviews has a weighty impact on research. Before devoting resources to original research that may impact patient care in the real world, reviewing what has been done to deliver improved outcomes can provide ideas for selecting variables for which data are available for use in our real-life setting.

Ovarian cancer is known by the feature of platinum resistance, which is associated with poor overall and progression-free survival. The use of genetic predictive biomarkers, principally BRCA mutations and other alterations in genes of repair pathways such as homologous recombination deficiency (HRD), is not accessible widely for routine use, particularly in resource-constricted settings. Promisingly, given the limited use of precision medicine in practices in low- and middle-income countries (LMICs) like mine, finding surrogate cost-effective biomarkers for patient stratification attracted my attention. I have conducted a first critical review on emerging circulating and tissular biomarkers for predicting prognosis and treatment sensitivity to select those that are promising for research in our setting.1 In addition to this perspective, reading a significant number of important publications for my literature review has helped me understand the biology and pathological patterns of this aggressive cancer. Following this first successful article published in Cellular Oncology, I started another critical review to have a deeper understanding of the field of predictive biomarkers for therapy response prediction in ovarian cancer with the aim to use those available in our regional cohort.2 These two writing experiences were very motivating and have significantly improved my skills in reviewing and appraising the literature. This has introduced me to the field of evidence-based medicine, which requires notable training in research methodology and biostatistics. I am reminded of a quote attributed to Marcus Aurelius: “Nothing has such power to broaden the mind as the ability to investigate systematically and truly all that comes under thy observation in life.”

Learn Universal Research Methodology First, Then Focus on Targeted Training

Conducting original studies in LMICs in the field of oncology requires advanced training on research methodology and biostatistics. This field is known by its particular methods used for studying cancer outcomes such as survival analysis using the Kaplan-Meier approach and Cox proportional hazards model, and also other inferential statistics such as receiver-operating characteristic used for accuracy studies. In high-income countries (HICs) and other high-resource settings, cancer studies are performed by a research team in which qualified data analysts and other researchers play a crucial role. A shortage of statisticians and data scientists that work in clinical sciences is an additional negative factor that affects the quality of research conducted in LMICs. I was therefore obliged to do things myself, from setting up my project to the publication of the results, without relying on the help of other contributors. I expended too much energy, time, and self-funding to have respectable training and have my ideas materialized in a real project. The beginning was marked by learning the general methods of epidemiology and biostatistics and later I have focused on particular methods adapted to my project objectives. This has notably improved my vision and skills to shape my project on ovarian cancer.

There are enjoyable books and guides, such as ESMO Handbook of Interpreting Oncological Study Publications, that enable us to see hidden information between lines of published ovarian cancer literature. In addition, various books offer simplified statistical methods for clinicians to be used in their research. Methods and Biostatistics in Oncology is another example of a good book that was prepared for use by oncologists desiring to appraise the literature and understand statistical tools adapted to cancer research. For more methods-oriented guides, I consulted the famous Clinical Epidemiology which was very useful in understanding epidemiological study designs. This book series provides cutting-edge techniques with step-by-step details for the design of observational and interventional studies. Last but not least, reading materials and methods sections of articles was also helpful in getting information for this purpose.

Pursuing Excellence

Fundamentally, excellence in clinical research requires high-quality patient data. Basically, you need prospective enrollment of patients with cancer to accurately account for the issue of missing data and provide good variables for hypothesis testing and adjustment for confounding. After the first signs of success of our OVANORDEST-1 study emerged, which was retrospective in its nature, we developed OVANORDEST-2 (see Part 1), a prospective trial designed to validate the encouraging findings of the previous feasibility real-world report. It also aims to explore potential blood-based biomarkers for ovarian cancer with prior statistical testing.

We designed this study after appraising the current evidence on some biomarkers using a systematic review approach. In order to select any biomarkers for developing prediction models, a critical evaluation of potential predictors should be performed. In this perspective, we published a PROSPERO-registered umbrella systematic review of 17 meta-analyses on the accuracy of some cost-effective inflammatory biomarkers that can be used to establish a prognostic score of overall and progression-free survival in epithelial ovarian cancer for settings with limited resources.3 We proceeded by appraising the quality of all published meta-analyses that explored these biomarkers associated with systemic inflammation—a hallmark of cancer—using the standard Assessment of Multiple Systematic Reviews (AMSTAR-2)4 tool and other qualitative parameters. We have also graded the evidence drawn from these meta-analyses to demonstrate the independent predictive value of these biomarkers for outcomes. We have finally concluded that the evidence from this review is weak and a prospective study should be conducted to improve the current evidence. Therefore, we included this in the study design of our prospective cohort.

This project was also supported by publishing a thematic issue on platinum-resistant ovarian cancer in Seminars in Cancer Biology. This special issue includes 14 papers from brilliant oncologists working in the field of ovarian cancer such Dr. Isabelle Ray-Coquard, Dr. Intidhar Labidi-Galy and Dr. Stephanie Lheureux who reviewed the clinical relevance of immune-checkpoint blockade and other new approaches for treating platinum-resistant ovarian cancer. Other invited reviews covered important and emerging topics in the field of cancer biology, biomarkers, and advances in therapy for this aggressive cancer, such as the evolving role of the fallopian tubes in the process of ovarian carcinogenesis, the possible future arrival of antibody-drug conjugates, the impact of tumor microenvironment, liquid biopsy, and debulking surgery in delivering improved ovarian cancer outcomes. The series includes four articles on genomics: lessons learned from BRCA mutations, prediction of platinum and PARP inhibitor response, mechanisms of resistance in epithelial ovarian cancer, and genomic profiling.

collection of journals and publications

The special issue of Seminars in Cancer Biology edited by our team, and some of our other publications.

I also edited a book with Springer Nature, Ovarian Cancer Biomarkers: Mapping to Improve Outcomes, that discusses the significant impact of prognostic and predictive biomarkers in personalizing and guiding ovarian cancer management. The book comprehensively explores precision medicine for ovarian cancer through seven chapters encompassing pathology, actionable ovarian cancer hallmarks, mechanisms of drug resistance, advances in its therapeutic management and cutting-edge molecular profiling technologies with a particular focus on biomarkers.

Book covers

Books developed by our research team.

These publications were of high importance as they bring experience to our research team in terms of international collaboration and visibility, as well as gaining familiarity with the peer-review system and academic editing and publishing—a crucial learning objective when training young researchers to have the skills for a career in academia.

Young oncologists working on research projects in resource-limited environments should be motivated to develop similar initiatives because of the advantages this can bring to their settings. You do not have to be an expert to begin—you can read, learn, and develop your skills as you go. The most important thing is simply to get started. As Nobel Prize winner Marie Curie said, “Have no fear of perfection; you’ll never reach it.”

Dr. El Bairi is a research associate in the Department of Medical Oncology at Mohammed VI University Hospital, in Oujda, Morocco, and he is preparing for a career in medical oncology. He joined the ASCO Trainee & Early Career Advisory Group as a member for the 2022-2023 term. The contents of this paper reflect the author's perspective and not that of his institution of affiliation. Follow Dr. El Bairi on Twitter @elbairikhalid19. Disclosure.


  1. El Bairi K, Kandhro AH, Gouri A, et al. Emerging diagnostic, prognostic and therapeutic biomarkers for ovarian cancer. Cell Oncol (Dordr). 2017;40:105-118.
  2. El Bairi K, Amrani M, Kandhro AH, et al. Prediction of therapy response in ovarian cancer: Where are we now? Crit Rev Clin Lab Sci. 2017;54:233-66.
  3. El Bairi K, Al Jarroudi O, Afqir S. Inexpensive Systemic Inflammatory Biomarkers in Ovarian Cancer: An Umbrella Systematic Review of 17 Prognostic Meta-Analyses. Front Oncol. 2021;11:694821.
  4. Shea BJ, Reeves BC, Wells G, et al. AMSTAR 2: a critical appraisal tool for systematic reviews that include randomised or non-randomised studies of healthcare interventions, or both. BMJ. 2017;358:j4008.


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