Prognostic Factors and Predictors of Disease Flare in Patients With Rheumatoid Arthritis
Conditions: Rheumatoid Arthritis Disease Flare
Sponsor: Sohag University

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Rheumatology & Rehabilitation Medicine Department 
                                                                                                                     Faculty of Medicine 
                                                                                                                       Sohag University 
 
Prognostic Factors and Predictors of Disease 
Flare in Patients with Rheumatoid Arthritis  
 
Protocol of thesis submitted for partial fulfillment of Ph.D degree in Rheumatology & 
Rehabilitation Medicine 
Presented by 
Esraa Mohamed Mahmoud Sayed 
(MSc., Faculty of Medicine, Sohag University) 
Supervised by 
Dr. Esam Mohamed Abo-Elfadl 
Professor of Rheumatology & Rehabilitation Medicine 
Faculty of Medicine, Sohag University 
 
Dr. Sahar Abd Elrahman Elsayed 
Assistant Professor of Rheumatology & Rehabilitation Medicine 
Faculty of Medicine, Sohag University 
 
Dr. Rana Nasser Saad-Eldin 
Lecturer of Rheumatology and Rehabilitation Medicine 
Faculty of Medicine, Sohag University 
Sohag University 
2026 
 

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Introduction 
 
Rheumatoid arthritis (RA) is a systemic autoimmune disease characterized 
by inflammatory synovitis, progressive joint destruction, and potentially extra-
articular involvement (Chauhan et al., 2025).  
RA treatment failure can lead to increased incidence of disease 
complications and severe functional disability(Wang et al., 2021). The American 
College of Rheumatology (ACR) and the European League Against Rheumatism 
(EULAR) have endorsed the treat-to-target strategy, aiming that the treatment of 
RA should target remission or low disease activity (LDA) in every patient, which 
has yielded superior treatment outcomes in comparison to standard care  (Smolen 
et al., 2016, 2020). If remission or LDA is reached, this state should be 
maintained. However, up to 30% of patients with RA experience flares (Bykerk 
et al., 2014). 
Although the concept of RA flare is yet to have a solid definition, it can be 
described as enhanced joint pain, joint swelling, and elevated levels of acute 
phase reactants (Oh et al., 2020). Flares are often reported to be associated with 
impaired physical function, increased fatigue, and reduced quality of life, as well 
as serious long-term sequelae, including incremental joint damage (Markusse et 
al., 2015). Despite their importance, RA flare patterns and predictors remain 
poorly understood and are challenging to investigate because of their sporadic 
and unpredictable nature. The ability to predict flares when patients reach 
remission or LDA could facilitate decisions regarding treatment maintenance or 
reduction (Rayner et al., 2024).  
On the other hand, emerging novel inflammatory biomarkers, such as the 
neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), 
systemic immune-inflammation index (SII), systemic inflammation response 
index (SIRI), and, more recently, pan-immune-inflammation value (PIV), have 
emerged as important indicators of systemic inflammation. Their role in disease 
flare prediction remains an area of recent research (SATIS, 2021; Tutan & 
Doğan, 2023). 
 
 
 
 
 
 
 
 

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Aims of the Work 
1. To identify clinical, serological, radiographic, and treatment-related 
predictors of disease flare in RA patients who have achieved persistent 
clinical remission or LDA. 
2. Evaluation 
of 
blood-cell-derived 
inflammatory 
indices: 
Neutrophil/lymphocyte ratio (NLR), Platelet/neutrophil ratio (PNR), 
Platelet/lymphocyte (PLR), Lymphocyte/monocyte ratio (MLR), Systemic 
Inflammatory Response Index (SIRI), Systemic Immune-inflammation 
index (SII), and Pan Immune Inflammation Value (PIV), in relation to 
disease flares in RA. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

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Patients and Methods 
 
Study approval:  
• This research will be revised by the Scientific Ethical Committee of the 
Faculty of Medicine-Sohag University.  
• Written informed consent will be obtained from all participants in the 
study. 
• Privacy and confidentiality of the patients’ data will be assured. 
 
Study design:  
• Prospective, observational cohort study 
 
Place of the study:  
• Rheumatology department, Sohag University Hospitals 
 
Inclusion criteria: 
• Age: patients >18 years old. 
• Patients with Rheumatoid arthritis diagnosed according to the 2010 
American College of Rheumatology (ACR)/European Alliance of 
Associations for Rheumatology Classification Criteria for RA (Kay & 
Upchurch, 2012). 
• Clinical remission or low disease activity according to the disease activity 
score in 28 joints (DAS28)(Fleishman et al., 2008). 
 
Exclusion criteria: 
• Age < 18 years. 
• Any autoimmune disease other than Rheumatoid arthritis. 
• Severe infection, pregnancy, and malignancy. 
 
 
 
 
 
 
 
 

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Study methodology: 
 
• This study will include all patients presenting to the Rheumatology 
department, Sohag University Hospitals, from February 1st, 2026, till June 
30th, 2027, and who were diagnosed with Rheumatoid Arthritis according 
to the 2010 American College of Rheumatology (ACR)/European Alliance 
of Associations for Rheumatology Classification Criteria for RA (Aletaha 
et al., 2010). 
 
The following data will be reviewed for each patient: 
1. Demographic data (e.g., age, gender, residence, marital status, 
socioeconomic status, etc.) 
2. Medical history and physical examination. 
3. Thorough rheumatological examination. 
4. Disease characteristics (disease duration, time to diagnosis, time to 
remission, time to starting DMARDs, radiographic disease state, and extra-
articular manifestations). 
5. Medication data will be collected. 
6. Follow up every 3 months for assessment of disease flare through the 
assessment of: 
a. Assessment of Tender Joints Count (TJC) and Swollen Joints 
Count (SJC). 
b. Assessment of Visual Analogue Scale (VAS). 
c. Patient and evaluator global assessments (PGA and EGA). 
d. Assessment of disease activity by DAS28, and SDAI 
scores(Aletaha & Smolen, 2007, 2009). 
e. ACR 20, ACR50, and ACR70 response: American College of 
Rheumatology criteria measuring treatment response 20%, 50% and 
70% of improvement (respectively)(Felson et al., 1998). 
f. Assessment of functional status by modified health assessment 
questionnaire (HAQ) (Anderson et al., 2010). 
g. Assessment of treatment adherence. 
h. Laboratory assessment of acute phase reactants (ESR and CRP) in 
addition to RF, ACPA, CBC, ALT, AST, serum creatinine, and 
blood urea nitrogen. 
 

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i. Blood-cell-derived inflammatory indices will be calculated for 
each patient at every follow-up visit: 
• Neutrophil/lymphocyte ratio (neutrophil count /lymphocyte 
count), 
• Platelet/neutrophil ratio (platelet count/neutrophil count). 
• Platelet/lymphocyte ratio (platelet count/lymphocyte count) 
• Lymphocyte/monocyte ratio (lymphocyte count/monocyte 
count) 
• Systemic Immune Inflammation index (neutrophil count x 
platelet count/lymphocyte count) 
• Systemic Inflammatory Response index: (neutrophil x 
monocytes/lymphocyte counts) 
• Pan-immune inflammatory response (monocytes x platelets x 
neutrophils/lymphocytes). 
j. Clinical evaluation of any newly emerging symptoms or signs 
suggesting any form of increased disease activity or extraarticular 
manifestations. 
k. Duration and frequency of disease flares for each patient 
l. Radiographic progression of disease as measured by the modified 
Sharp scoring system (van der Heijde et al., 1989). 
Flare was defined as an increase in DAS28 compared with baseline of >1.2 or 
>0.6 if concurrent DAS28 ≥3.2 (van der Maas et al., 2013). 
 
 
Statistical analysis:  
Statistical analysis will be performed using SPSS software (version 26.0 or later, 
IBM Corp., Armonk, NY, USA). Continuous variables will be expressed as mean 
± standard deviation, and categorical variables as frequencies and percentages. 
Independent samples t-test or Mann-Whitney U test will be used to compare 
continuous variables between groups, while chi-square test or Fisher's exact test 
will be used for categorical variables. Pearson’s or Spearman's correlation 
coefficient will be used to assess correlations between continuous variables. (p-
value considered significant if < 0.05). Other statistical analyses will be done if 
needed.  
 
 
 

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