Rheumatology

This Article Abstract FREE Full Text (PDF) Alert me when this article is cited Alert me if a correction is posted Services Email this article to a friend Similar articles in this journal Similar articles in ISI Web of Science Similar articles in PubMed Alert me to new issues of the journal Add to My Personal Archive Download to citation manager Search for citing articles in: ISI Web of Science (42) Request Permissions Disclaimer Google Scholar Articles by Chehata, J. C. Articles by Dawes, P. T. Search for Related Content PubMed PubMed Citation Articles by Chehata, J. C. Articles by Dawes, P. T. Related Collections Rheumatoid Arthritis Social Bookmarking          What's this?

Rheumatology 2001; 40: 447-452
© 2001 British Society for Rheumatology

Mortality in rheumatoid arthritis: relationship to single and composite measures of disease activity

J. C. Chehata, A. B. Hassell, S. A. Clarke, D. L. Mattey, M. A. Jones¹, P. W. Jones² and P. T. Dawes

Staffordshire Rheumatology Centre, The Haywood, Stoke-on-Trent,
¹ Directorate of Public Health, North Staffordshire Health Authority, Stoke-on-Trent and
² Keele University, Keele, UK

	Abstract

Top Abstract Introduction Methods Results Discussion References

 
Background. Rheumatoid arthritis (RA) is a heterogeneous disease characterized by a variable course of remissions and relapses. Single measures of disease activity at only one point in time may not reflect the overall control of disease activity.

Objective. The aim was to determine (i) the predictive value of 20 baseline demographic and disease variables on mortality, and (ii) the relationship between serial measures of the Stoke index (SI; a validated index of disease activity in RA) and mortality in RA.

Methods. Mortality in 309 RA patients followed up for a median of 14 yr was analysed retrospectively. The standardized mortality ratio (SMR) was calculated for all causes of death. The predictive values of baseline and time-integrated variables were assessed using multivariate Cox proportional hazards regression analysis.

Results. The SMR was 1.65. At baseline, only nodules, erosions, RA latex titre, white cell count and globulin level were predictive of mortality after correction for age, sex and disease duration. Using a stepwise Cox proportional hazards regression model, the most powerful predictors of mortality were age, nodules and RA latex titre. Individual measures of disease activity and the SI at baseline were not predictive of mortality. However, the mean level of the SI over 12 months was related to mortality (P=0.039).

Conclusions. At baseline, the demographic and disease variables most significantly related to mortality in RA are age, nodules and RA latex titre. Individual measures of disease activity at a single point in time are poor predictors of mortality in RA. However, measurement of the mean level of disease activity over time using the composite SI has a significant relationship with mortality. A high level of sustained inflammation appears to be an important predictor of premature death.

KEY WORDS: Rheumatoid arthritis, Mortality, Stoke index.

	Introduction

Top Abstract Introduction Methods Results Discussion References

 
A number of studies have shown that rheumatoid arthritis (RA) is associated with reduced lifespan and excess mortality [1–6]. The causes of death in RA are generally non-articular, the relationship to comorbidity factors being speculative. In a large series of 2262 deaths of patients with RA, approximately 40% of the deaths were attributed to cardiovascular causes [7]. Excess deaths in RA patients are also due to infection, renal, respiratory and gastrointestinal disease [8]. Work by Symmons et al. [9] suggests that excess malignancy, especially neoplasms of the immune system, also contributes to the excess mortality.

Disease measures in RA fall into two broad groups: reversible measures of inflammatory disease activity, such as joint scores and serum C-reactive protein (CRP) levels; and irreversible measures of damage, such as X-ray scores [10, 11]. Some measures reflect both disease activity and damage, for example grip strength and functional status questionnaires [11]. RA outcomes include both damage and death.

The relationship between disease activity measures and outcome is controversial. Callahan et al. [12] found that measures of disease activity taken at the beginning and end of 5 yr of follow-up were either unchanged or better whereas measures of damage were worse, and they concluded that measures of disease activity may underestimate long-term outcome. Conversely, Hassell et al. [13] found a significant correlation between disease activity, as measured by serial measurements (area under the curve) over 5–9 yr, and outcome assessed by radiographic deterioration and measures of function. Measures at a single time-point did not predict outcome. Studies of mortality in RA so far have included single measures of disease activity at only one point in time [6, 12, 14], and could be influenced by temporary flare-ups or remissions and may not reflect the overall level of disease activity.

The main purpose of this study was to address the question of whether there is a relationship between measures of disease activity over a period of time and subsequent mortality. In addition, we assessed the value of 20 baseline demographic and disease variables as predictors of mortality.

	Methods

Top Abstract Introduction Methods Results Discussion References

 
Patients
Three hundred and nine RA patients were recruited consecutively from the Staffordshire Rheumatology Centre out-patient clinics for prospective non-commercial studies of drug therapies between 1981 and 1985. The Rheumatology Centre serves a population of 475 000. Approximately 3500 RA patients (0.74%) are registered and reviewed annually at this centre. At the time of recruitment, all patients satisfied the 1958 ARA criteria for the diagnosis of RA [15]. Table 1 shows the number of patients on each drug and the reason for discontinuation in the first year. Although these drug studies did not include cytotoxic agents, some of the patients subsequently received methotrexate, azathioprine or cyclophosphamide. All patients were followed until either 8 October 1998, the time of death or the date last seen.

View this table: [in this window] [in a new window]   TABLE 1. Number of patients on each drug and the reason for discontinuation in the first year of the drug studies

 

Baseline measures
Twenty variables assessed at recruitment were studied in relation to survival. These included the demographic data of age, sex and disease duration, and the clinical and laboratory data of morning stiffness, grip strength, painful joint score, synovitis score of the proximal interphalangeal joints (PIP), the Ritchie articular index (a score of tender joints), pain measured on a visual analogue scale (VAS), the presence of nodules, erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), haemoglobin level, white cell count, platelet count, albumin, total globulin and alkaline phosphatase levels, presence of erosions on plain X-rays of the hands and feet, and RA latex (RAL) titre. Plain X-rays of the hands and feet were scored independently at entry for the presence of erosions by two rheumatologists experienced in X-ray scoring, without prior knowledge of the treatment allocated. All clinical measures (PIP score, Ritchie index, etc.) were performed by two trained metrologists throughout the studies, with no significant differences in their inter- and intra-rater reliabilities.

Serial measures
The Stoke index (SI) is a validated measure for disease activity in RA [16]. It grades disease activity on the basis of PIP score, ESR, morning stiffness, CRP and the Ritchie index. The index consists of a 17-point scale, 1–3 representing minimal disease activity, 4–7 mild activity, 8–11 moderate activity and 12–17 severe activity. A summary measure for the serial readings can be either the overall mean (with equal time intervals) or the area under the curve (with unequal time intervals) [17]. In this study we used the mean value of the SI readings because they were taken at equal time intervals.

The mean of the SI readings was calculated for every patient 0 and 6 months after recruitment, while the mean of the SI at 0, 6 and 12 months was calculated for a subgroup of 213 patients. This was because one patient died, two were lost to follow-up and the SI data were incomplete for 93 patients, among whom 79 dropped out of the initial drug studies to which they had been recruited. The outcome data of the latter patients were still available as these patients were subsequently seen in the outpatient clinics. These 96 patients were not significantly different from the subgroup of 213 patients as regards age, disease duration and the mean SI at recruitment, but included significantly more female patients.

Statistical methods
The age- and sex-specific mortality rates for England and Wales for each year of the study period were applied to appropriate patient-years at risk to calculate the expected number of deaths. The standardized mortality ratio (SMR; ratio of observed to expected deaths) and its 95% confidence interval were calculated for all causes of death.

The paired t-test was used to compare the mean SI between 0 and 6 months and between 0 and 12 months. The predictive value of each baseline variable and the SI at time 0 for mortality was assessed in a Cox proportional hazards regression analysis that included age, sex and disease duration, as suggested by Symmons et al. [18]. The time intervals for those patients who were alive at the end of the study period and those who were lost to follow-up were treated as censored. A stepwise routine using all the variables measured at baseline was used to define the most powerful independent predictors. The predictive value of the means of the SI and its components measured at 0 and 6 months for every patient in the whole group and at 0, 6 and 12 months for the subgroup of 213 patients was also assessed in a Cox proportional hazards regression analysis corrected for age, sex and disease duration.

Kaplan–Meier curves were constructed in order to illustrate how survival was related to some categorical baseline variables. Age, disease duration and rheumatoid factor titre were each divided into three categories: age (<40, 40–60 and >60 yr), disease duration (<5, 5–10 and >10 yr) and rheumatoid factor (negative, 1:80 and >1:80). Curves were also constructed for the rounded up means of the SI over the 6- or 12-month period following recruitment using the same categories as in the algorithm originally suggested by Jones et al. [16]. Only the curves for age, sex and disease duration were compared using the log rank significance tests, as the relation of the other variables to survival was assessed in the Cox regression model.

	Results

Top Abstract Introduction Methods Results Discussion References

 
Demographic and baseline characteristics
In this group of 309 RA patients, 189 were female (62%). At recruitment the median age was 53 yr (range 19–74) and the median disease duration was 30 months (range 3–396). Patients were followed up for a median of 14.12 yr (range 0.56–18.3). The total number of deaths was 109 (35%). Twenty-one patients were lost to follow-up. Table 2 shows the means and standard deviations of the continuous baseline disease variables and the SI at recruitment.

View this table: [in this window] [in a new window]   TABLE 2. Baseline continuous variables

 

Mean values of the SI at 0, 6 and 12 months
Compared with baseline, the mean SI showed a highly significant reduction at 6 months (8.3 vs 5.4, P<0.0001) and at 12 months (8.5 vs 4.2, P<0.0001).

Mortality
In this group of RA patients, the observed number of deaths significantly exceeded the expected number. The observed and expected numbers of deaths and the SMR for the whole group, males and females are shown in Table 3.

View this table: [in this window] [in a new window]   TABLE 3. Number of deaths and SMR in a cohort of 309 patients with RA

 

Factors predictive of survival
Table 4 shows the results of the Cox regression analysis corrected for age, sex and disease duration for the baseline variables with significant (or nearly significant) predictive value for mortality. Variables not shown in this table were not significantly related to mortality (P>0.1). When the rheumatoid factor titre was computed for positivity only (i.e. either positive or negative regardless of titre), the result was not significant. In the stepwise model, age, the presence of nodules and RAL titre were the most powerful independent predictors. For every year increase in age, the hazard of death was increased by 8%. The presence of nodules doubled the hazard of death and for every increase of 100 in the reciprocal value of the RAL titre the hazard of death was increased by 9% (Table 5).

View this table: [in this window] [in a new window]   TABLE 4. Baseline variables at recruitment as predictors of mortality

 

View this table: [in this window] [in a new window]   TABLE 5. Baseline variables chosen by the stepwise Cox proportional hazards model as the most powerful independent predictors of mortality with inclusion P value 0.05

 
Table 6 shows that the mean SI taken over a 6-month (n=309) or 12-month (n=213) period after recruitment was significantly related to mortality (P=0.045 and P=0.039 respectively), although individual components of the SI were not.

View this table: [in this window] [in a new window]   TABLE 6. Mean SI and its components over 6- and 12-month periods as predictors of mortality corrected for age, sex and disease duration (Cox regression analysis)

 

Survival analysis: Kaplan–Meier curves
Survival probability curves were constructed for some of the baseline variables (Fig. 1). The difference in survival between the three age groups was highly significant (P<0.001; log-rank test). Although survival was lower for male than for female patients, the difference was not significant (P=0.1). The difference in survival between categories of disease duration approached significance (P=0.08). The curves also illustrate reduced survival with a higher level of rheumatoid factor, with the presence of erosions on the plain X-ray film and with the presence of rheumatoid nodules at recruitment. Figure 2 illustrates reduced survival with higher levels of disease activity, represented by higher scores of the mean SI over a 6- or 12-month period.

View larger version (17K): [in this window] [in a new window]   FIG. 1. Survival probability according to some baseline variables. (a) Age. (b) Sex. (c) Disease duration. (d) Presence of nodules. (e) Presence of erosions. (f) Rheumatoid factor.

 

View larger version (14K): [in this window] [in a new window]   FIG. 2. Survival probability according to the mean SI. (a) At 0 and 6 months (n=309). (b) At 0, 6 and 12 months (n=213).

 

	Discussion

Top Abstract Introduction Methods Results Discussion References

 
RA is a heterogeneous disease characterized by remissions and relapses and a variable outcome. The SMR in our study was similar to those in previous hospital-based studies [19]. Measures of disease activity in RA are generally thought to reflect short-term control of the disease. Their relation to long-term outcomes such as mortality is controversial. In a 25-yr prospective study of 100 patients, Reilly et al. [14] found no significant difference in mean ESR, haemoglobin or joint score at baseline between 21 patients who died of RA-related causes and 77 other patients (35 survivors and 42 deaths thought to be unrelated to RA). On the other hand, Scott et al. [20] found that a high initial ESR (>50) and seropositivity (Rose–Waaler titre >1/64) were related to a poor outcome, as assessed by the functional class and mortality after 20 yr, although their predictive values were not strong. Callahan et al. [12] found a significant difference between dead and surviving patients after 5 yr as regards the baseline total joint count and ESR but not the rheumatoid factor titre.

In our study we assessed the predictive value of individual baseline disease variables in a Cox proportional hazards regression model corrected for age, sex and disease duration. We found that, in addition to age, two clinical markers of disease severity in RA, i.e. nodules and RAL titre, were powerful independent predictors of mortality. Similar findings were reported by Wolfe et al. [6]. We also found that rheumatoid factor positivity alone is not predictive of mortality but that the titre is predictive. These findings confirm that rheumatoid nodules and a high RAL titre may be markers of a more severe underlying pathological process. The significant predictive value of the white cell count and globulin level for mortality in our study is difficult to interpret. However, slight leucocytosis with a normal differential count can be an initial finding in RA [21]. Furthermore, Wolfe et al. [22] also found recently that the white cell count predicted mortality in 1865 consecutive RA patients followed up for 25 yr. It should be pointed out that in our model some other demographic and clinical variables were not included (e.g. socioeconomic factors, comorbid factors, etc) because of unavailability or practical difficulties in collecting the data. The HAQ (health assessment questionnaire) score had not been accepted extensively before our studies began. The Steinbroker score was evaluated but was too crude a measure to show differences both within and between individuals.

In a disease with a variable, heterogeneous course, measures of activity at a single point in time can be influenced by temporary flare-ups and remissions and might not reflect the overall control of activity. Moreover, it has been appreciated previously that no single laboratory or clinical measure alone accurately reflects the disease status. A number of indices that incorporate several variables have been designed. The SI is a well-validated index of disease activity based on five variables [16]. Hassell et al. [13] found a strong correlation between serial measurements (mean area under the curve) of the SI and measures of outcome (radiological, functional and global assessment). In our study, individual measures of disease activity and the SI at baseline were not predictive of mortality. However, the mean SI taken over a 6- or 12-month period was significantly related to mortality (P=0.045 and 0.039 respectively). Kaplan–Meier curves showed reduced survival with increased severity of disease activity, as assessed by the mean SI. The SI was constructed with potentially reversible measures of inflammatory disease, and our results show that the level of sustained inflammation is important in relation to premature death. Recently, Krause et al. [23] demonstrated a>4-fold increase in mortality (SMR 4.11) in patients with severe RA who did not show improvement after 1 yr of methotrexate treatment. Those with 20% improvement had only a moderate increase in mortality rate (SMR 1.64). Response criteria included the number of swollen joints, ESR, daily steroid dose and the patient's assessment of disease activity.

In less complex diseases, inflammation has also been related to mortality. In 188 consecutive patients selected for thrombolytic therapy, Pietila et al. [24] found that the mean value of the highest serum CRP concentration (observed 2–4 days after the infarction) was significantly higher in patients who died within 3 and 3–6 months after the infarction than in those who survived the whole 24-month study period. The highest serum concentrations of creatine kinase or its MB isoenzyme were not associated with mortality. They concluded that reduction of the inflammatory process by successful thrombolytic treatment might make an important contribution to the survival benefit of thrombolytic treatment. Similarly, Muir et al. [25] found that, in 228 consecutive patients with ischaemic stroke followed up for a median of 959 days, a higher CRP concentration measured within 72 h of the stroke was an independent predictor of mortality.

In summary, our study confirms that, in addition to age, nodules and a high rheumatoid factor titre are markers of poor prognosis in RA. We have also demonstrated an important relationship between sustained disease activity in RA and mortality. A low level of disease activity within the first year after recruitment was associated with better survival in this group of RA patients. This could be due to either therapeutic control or reduced disease activity. Assessment of the relationship between disease activity over longer periods of time and mortality are needed to confirm our findings. Although there was a significant improvement in the SI 6 and 12 months after recruitment to the drug studies, it was not the aim of this study to directly assess the relationship between response to treatment and mortality. Nonetheless, our findings suggest that sustained control of disease activity will improve not only the quality but also the length of life.

	Acknowledgments

 
This research was supported by the Haywood Rheumatism Research and Development Foundation.

	Notes

 
Correspondence to: J. C. Chehata, Department of Rheumatology, The Haywood, High Lane, Burslem, Stoke-on-Trent ST6 7AG, UK.

	References

Top Abstract Introduction Methods Results Discussion References

 

1. Cobb S, Anderson F, Bauer W. Length of life and cause of death in rheumatoid arthritis. N Engl J Med1953; 249:553–6.[Web of Science][Medline]
2. Duthie JJR, Brown PE, Truelove LH, Baragar FD, Lawrie AJ. Course and prognosis in rheumatoid arthritis: a further report. Ann Rheum Dis1964;23:193–202.[Free Full Text]
3. Allebeck P, Ahlbom A, Allander E. Increased mortality among persons with rheumatoid arthritis, but where RA does not appear on death certificate. Scand J Rheumatol1981;10:301–6.[Web of Science][Medline]
4. Rasker JJ, Cosh JA. The natural history of rheumatoid arthritis over 20 years. Clinical symptoms, radiological signs, treatment, mortality and prognostic significance of early features. Clin Rheumatol1987;6(Suppl. 2):5–11.[Medline]
5. Rasker JJ, Cosh JA. Course and prognosis of early rheumatoid arthritis. Scand J Rheumatol 1989 (Suppl.) 79:45–60.
6. Wolfe F, Mitchell DM, Sibley JT et al. The mortality of rheumatoid arthritis. Arthritis Rheum1994;37:481–94.[Web of Science][Medline]
7. Pincus T, Callahan LF. Taking mortality in rheumatoid arthritis seriously-predictive markers, socio-economic status and comorbidity. J Rheumatol1986;13:841–5.[Web of Science][Medline]
8. Symmons DPM. Mortality in rheumatoid arthritis. Br J Rheumatol1988;27(Suppl. 1):44–54.
9. Symmons DPM, Jones MA, Scott DL, Prior P. Long term mortality outcome in patients with rheumatoid arthritis: early presenters continue to do well. J Rheumatol1998; 25:1072–7.[Web of Science][Medline]
10. Dawes PT, Davis MJ, Jones P, Ziade F. Monitoring of rheumatoid arthritis. Lancet1989;2:1219.[Medline]
11. Pincus T, Callahan LF. Prognostic markers of activity and damage in rheumatoid arthritis: why clinical trials and inception cohorts studies indicate more favourable outcomes than studies of patients with established disease. Br J Rheumatol1995;34:196–7.[Free Full Text]
12. Callahan LF, Pincus T, Huston JW et al. Measures of activity and damage in rheumatoid arthritis: Depiction of changes and prediction of mortality over five years. Arthritis Care Res1997;10:381–94.[Web of Science][Medline]
13. Hassell AB, Davis MJ, Fowler PD et al. The relationship between serial measures of disease activity and outcome in rheumatoid arthritis. Q J Med1993;86:601–7.[Web of Science][Medline]
14. Reilly PA, Cosh JA, Maddison PJ, Rasker JJ, Silman AJ. Mortality and survival in rheumatoid arthritis: a 25 year prospective study of 100 patients. Ann Rheum Dis1990;49:363–9.[Abstract/Free Full Text]
15. Ropes MW, Bennett GA, Cobb A, Jacox RF, Jessar RA. Revision of diagnostic criteria for rheumatoid arthritis. Bull Rheum Dis1958;9:175–6.[Medline]
16. Jones PW, Ziade MFM, Davis MJ, Dawes PT. An index of disease activity in rheumatoid arthritis. Stat Med1993;12:1171–81.[Medline]
17. Matthews JNS, Altman DG, Campbell MJ, Royston P. Analysis of serial measurements in medical research. Br Med J1990;300:230–5.[Abstract/Free Full Text]
18. Symmons DPM, Prior P, Scott DL, Brown R, Hawkins CF. Factors influencing mortality in rheumatoid arthritis. J Chronic Dis1986;39:137–45.[Web of Science][Medline]
19. Myllykangas-Luosujarvi RA, Aho K, Isomaki HA. Mortality in rheumatoid arthritis. Semin Arthritis Rheum1995;25:193–202.[Web of Science][Medline]
20. Scott DL, Symmons DPM, Coulton BL, Popert AJ. Long-term outcome of treating rheumatoid arthritis: results after 20 years. Lancet1987;May 16:1:1108–11.[Web of Science][Medline]
21. Harris ED. Clinical features of rheumatoid arthritis. In: Kelley WN, Harris ED, Ruddy S, Sledge CB, eds. Textbook of rheumatology, Vol. 1, edn 4. Philadelphia: W.B. Saunders, 1993:874–911.
22. Wolfe F, Hawley DJ, Anderson J, Wichita KS. All causes and cause specific mortality in rheumatoid arthritis (RA): A 25 year study of 1865 RA patients. Arthritis Rheum1999;42(Suppl.):S135.
23. Krause D, Schleusser B, Herborn G, Rau R. Response to methotrexate treatment is associated with reduced mortality in patients with severe rheumatoid arthritis. Arthritis Rheum2000;43:14–21.[Web of Science][Medline]
24. Pietila KO, Harmoinen AP, Jokiniitty J, Pasternack AI. Serum C-reactive protein concentration in acute myocardial infarction and its relationship to mortality during 24 months of follow-up in patients under thrombolytic treatment. Eur Heart J1996;17:1345–49.[Abstract/Free Full Text]
25. Muir KW, Weir CJ, Alwan W, Squire IB, Lees KR. C-reactive protein and outcome after ischaemic stroke. Stroke1999;30:981–5.[Abstract/Free Full Text]

Submitted 28 March 2000; revised version accepted 14 November 2000.
CiteULike    Connotea    Del.icio.us    What's this?

This article has been cited by other articles:

				B. ABELSON, T. SOKKA, and T. PINCUS Declines in Erythrocyte Sedimentation Rates in Patients with Rheumatoid Arthritis Over the Second Half of the 20th Century J Rheumatol, August 1, 2009; 36(8): 1596 - 1599. [Abstract] [Full Text] [PDF]

				B. Hameed, J. Pilcher, C. Heron, and P. D. W. Kiely The relation between composite ultrasound measures and the DAS28 score, its components and acute phase markers in adult RA Rheumatology, April 1, 2008; 47(4): 476 - 480. [Abstract] [Full Text] [PDF]

				T. M Farragher, M. Lunt, D. K Bunn, A. J Silman, and D. P M Symmons Early functional disability predicts both all-cause and cardiovascular mortality in people with inflammatory polyarthritis: results from the Norfolk Arthritis Register Ann Rheum Dis, April 1, 2007; 66(4): 486 - 492. [Abstract] [Full Text] [PDF]

				A. Young, G. Koduri, M. Batley, E. Kulinskaya, A. Gough, S. Norton, J. Dixey, and on behalf of the Early Rheumatoid Arthritis Study Mortality in rheumatoid arthritis. Increased in the early course of disease, in ischaemic heart disease and in pulmonary fibrosis Rheumatology, February 1, 2007; 46(2): 350 - 357. [Abstract] [Full Text] [PDF]

				G. Kobelt, P. Lindgren, Y. Lindroth, L. Jacobson, and K. Eberhardt Modelling the effect of function and disease activity on costs and quality of life in rheumatoid arthritis Rheumatology, September 1, 2005; 44(9): 1169 - 1175. [Abstract] [Full Text] [PDF]

				D L Mattey, N Nixon, P T Dawes, and J Kerr Association of polymorphism in the transforming growth factor {beta}1 gene with disease outcome and mortality in rheumatoid arthritis Ann Rheum Dis, August 1, 2005; 64(8): 1190 - 1194. [Abstract] [Full Text] [PDF]

				N. T. James, C. W. Miller, K. C. Brown, and M. Weaver Pain Disability Among Older Adults With Arthritis J Aging Health, February 1, 2005; 17(1): 56 - 69. [Abstract] [PDF]

				N. J. Goodson, A. J. Silman, D. J. Pattison, M. Lunt, D. Bunn, R. Luben, N. Day, K.-T. Khaw, and D. P. M. Symmons Traditional cardiovascular risk factors measured prior to the onset of inflammatory polyarthritis Rheumatology, June 1, 2004; 43(6): 731 - 736. [Abstract] [Full Text] [PDF]

				G. D. Kitas and N. Erb Tackling ischaemic heart disease in rheumatoid arthritis Rheumatology, May 1, 2003; 42(5): 607 - 613. [Full Text] [PDF]

				N Goodson and D Symmons Rheumatoid arthritis in women: still associated with an increased mortality Ann Rheum Dis, November 1, 2002; 61(11): 955 - 956. [Full Text] [PDF]

				T R Mikuls, K G Saag, L A Criswell, L A Merlino, R A Kaslow, B J Shelton, and J R Cerhan Mortality risk associated with rheumatoid arthritis in a prospective cohort of older women: results from the Iowa Women's Health Study Ann Rheum Dis, November 1, 2002; 61(11): 994 - 999. [Abstract] [Full Text] [PDF]

				M. L. Grove, J. C. Chehata, P. W. Jones, D. L. Mattey, and P. T. Dawes Re: Chehata et al. Mortality in rheumatoid arthritis: relationship to single and composite measures of disease activity Rheumatology, June 1, 2002; 41(6): 701 - 701. [Full Text] [PDF]

This Article Abstract FREE Full Text (PDF) Alert me when this article is cited Alert me if a correction is posted Services Email this article to a friend Similar articles in this journal Similar articles in ISI Web of Science Similar articles in PubMed Alert me to new issues of the journal Add to My Personal Archive Download to citation manager Search for citing articles in: ISI Web of Science (42) Request Permissions Disclaimer Google Scholar Articles by Chehata, J. C. Articles by Dawes, P. T. Search for Related Content PubMed PubMed Citation Articles by Chehata, J. C. Articles by Dawes, P. T. Related Collections Rheumatoid Arthritis Social Bookmarking          What's this?

Online ISSN 1462-0332 - Print ISSN 1462-0324

Copyright © 2009 British Society for Rheumatology

Oxford Journals Oxford University Press

• Site Map
• Privacy Policy
• Frequently Asked Questions

Other Oxford University Press sites: Oxford University Press Oxford Journals China Oxford Journals Japan American National Biography Booksellers' Information Service Children's Fiction and Poetry Children's Reference Corporate & Special Sales Dictionaries Dictionary of National Biography Digital Reference English Language Teaching Higher Education Textbooks Humanities International Education Unit Law Medicine Music Online Products Oxford English Dictionary Reference Rights and Permissions Science School Books Social Sciences Very Short Introductions World's Classics