Discussion
A new prediction tool for the risks of tophi formation amongst gout
patients was developed and validated in this study. The nomogram
consisted of nine easily available variables, including hospitalisation
frequency, disease duration, number of joints involved in gouty
arthritis, gout flares frequency, smoking, and whether combined with
atherosclerosis, diabetes, hypertension and kidney dysfunction. Through
the analysis using C-index and calibration plot alongside internal
verification, the nomogram was verified to have good discrimination and
calibration ability, and could be widely used in gout patients to
relatively accurately predict the risks of tophi
formation.22
Based on the results of predictor analysis, the nomogram demonstrated
that hospitalisation for more than twice per year, disease duration of
more than ten years, more than three joints involved in gouty arthritis,
frequency of gout flares for more than twice per year, smoking, and
combined with atherosclerosis, diabetes, hypertension and kidney
dysfunction could be the predictive factors for tophi formation. Amongst
the nine risk factors, most were consistent with the results of previous
studies.2,23 A retrospective clinical study involving
5,693 Chinese gout patients depicted a significant difference
(P<0.05) between the tophi and non-tophi groups with regard to
disease duration (10.28±7.54 years vs. 5.11±6.06 years), number of
joints involved (3.11±2.15 vs. 1.81±1.35), systolic pressure
(138.53±19.46 mmHg vs. 133.87±17.93 mmHg), diastolic pressure
(89.55±12.73 mmHg vs. 87.48±11.77 mmHg) and creatinine clearance rate
(Ccr) (93.05±48.7 mL/min vs. 106.61±51.76 mL/ min).2This study’s results were similar to those findings, which might be
explained by certain reasons. First of all, tophi is one of the
manifestations of chronic gout as a deposition of uric acid
crystals.24 Similar to other chronic metabolic
diseases, a longer gout duration entails more severe conditions, leading
to more joints involved in gouty arthritis, more frequent gout flare and
hospitalisation, as well as a higher probability of tophi formation.
Secondly, previous studies have discussed that uric acid can increase
blood pressure through damaging the vascular endothelium, activating the
renin angiotensin aldosterone system, and reducing the nitric oxide
levels in endothelium.25 Meanwhile, hypertension can
damage the renal blood perfusion and lead to tissue hypoxia, thus
reducing the uric acid clearance rate. Therefore, a more severe gout
leads to a higher risk of hypertension.26 Likewise, a
more serious hypertension denotes a more likelihood to cause kidney
damage and a less excreted uric acid that entails a higher risk of tophi
formation.27 In addition, previous researches have
indicated that smokers and diabetic patients have higher uric acid
concentrations, which can lead to vascular endothelial dysfunction, thus
increasing the risk of atherosclerosis, renal dysfunction and tophi
formation.28-30
Based on the aforementioned risk factors, it is of great significance to
enable certain measures to prevent and control tophi formation at an
early stage. According to the nomogram, for patients with longer gout
duration, apart from paying attention to controlling the blood uric acid
level and reducing gout flare frequency as well as the number of joints
involved in gouty arthritis, we should also highly consider monitoring
blood glucose, blood pressure, renal function and vascular conditions in
order to reduce the risks of tophi formation. For patients who already
have the aforementioned risk factors, early diagnosis and treatment of
tophi is necessary to avoid significant tophi-related complications such
as irreversible joint deformity and dysfunction, bone destruction and
fracture, infection and ulceration.
A series of steps had been undertaken to minimise potential bias in this
study. Firstly, for patients who have been hospitalised more than once,
only the data from the first hospitalisation were included to avoid
inclusion of repeated cases. In the electronic medical record system,
patients diagnosed with ‘gout’ or ‘gouty arthritis’ were searched using
keywords or ICD codes to avoid missing patients, which might cause
selection bias. Finally, uncertain data that were recorded in the
hospital system were reconfirmed by contacting the patients to ensure
data accuracy.
Despite the above measures, there are still some limitations in the
current study. First of all, the sample size was relatively small; most
subjects were male, and came from Zhejiang Province, China.
Additionally, the sample size of the tophi group was small, which might
limit the power of the regression analysis. Secondly, the predictive
model might not have included all potential factors related to tophi
formation. Since all data were collected from medical records of
discharged patients during hospitalization, some variables such as serum
uric acid and body mass index, might not represent patients’ actual uric
acid and weight control. Besides, certain demographics such as family
history and smoking or drinking history might be inconsistent with the
actual situation, due to patients’ intentional concealment or
unintentional false memories. Thirdly, despite the efforts to examine
the robustness of the nomogram by internal verification using a
bootstrap test, it is still possible that the nomogram is not quite
useful for gout populations in other regions and countries. Hence, an
external validation in wider populations is necessary in future studies.