Trajectories in quality of life of patients with a fracture of the distal radius or ankle using latent class analysis

This was the first study using latent class trajectory analyses to identify QOL trajectories (i.e., classes) in patients with a DRF or AF up to 12 months after fracture. In addition, we explored if these patient groups differed on sociodemographic, clinical, and psychological variables (i.e., biopsychosocial approach). The acquired knowledge can facilitate the identification of patients that might need additional monitoring or care.

Subgroups were characterized by several sociodemographic variables of which clinicians are advised to take notice of when treating patients with AF or DRF: i.e., age, sex, marital status, educational level, and employment status. Prior research on AF and DRF in relation to HS and HRQOL reported mainly inconsistent findings on the role of sociodemographic variables [21, 22]. Generally, we found that patients in the lower QOL trajectories (i.e., overall, physical, and environmental) were older. The proportion of women was higher in the lower physical and psychological QOL trajectories. Two studies in AF and DRF are mainly in agreement with these results suggesting that women are at risk for lower HS after fracture [53, 54]. In addition, patients in the higher QOL trajectories more frequently had a partner, showing protective value of the presence of a significant other. Furthermore, a higher educational level (i.e., except for social QOL) and higher job participation were found in the trajectories representing higher QOL. The positive association of educational level with QOL was also reflected in two studies on DRF and AF that reported lower physical HS in patients with lower formal education [55, 56].

Previous research was inconclusive on the role of clinical variables [21, 22] but our study suggests an important distinction between injury-specific and general clinical variables. The QOL trajectories showed no significant differences on injury-specific variables: fracture diagnosis (DRF versus AF), type of treatment (operative versus non-operative treatment), and AO classification. The finding that diagnosis was not significant could be explained by the use of the WHOQOL-BREF, a generic QOL instrument. This instrument is completed by the patient (subjective), but also contains items about the level of satisfaction (e.g., ‘How much do you enjoy life?’) and to what extent a patient is bothered (subjective), instead of items (e.g., ‘Are you able to walk the stairs) that could be considered objective items, because they could be completed by someone else by observing the patient’s functioning. Only general clinical variables (i.e., chronic comorbidities and smoking) were significantly related to class membership. Percentages of chronic comorbidities were 1.8 (i.e., social QOL) to 4.5 (i.e., physical QOL) higher in the lowest QOL class compared to the highest QOL class.

The importance of personality was confirmed. Patients in the trajectories representing lower QOL (i.e., all QOL domains and the overall facet), had higher trait anxiety and neuroticism scores but lower scores on extraversion. Our results are in line with prior research [23‐25]. However, one study [57] found no significant relationship between neuroticism and functional status in DRF assessed with the Disabilities of Arm, Shoulder, and Hand (DASH) questionnaire [58]. However, we hypothesize that the relationship between personality is stronger for multidimensional outcome measures that take psychosocial functioning into consideration as well (i.e., HS and (HR)QOL measures) [20]. How satisfied patients are with their functioning (HR)QOL, in contrast to an assessment of functioning (HS), might be particularly influenced by enduring patterns in behavior, cognition, and emotion that is labeled personality [59].

Pain catastrophizing is an important health cognition to take into account when treating DRF and AF. Higher pain catastrophizing was found in trajectories representing lower QOL (i.e., all QOL domains and the overall QOL facet). Those few studies that reported on pain catastrophizing in relation to HS/HRQOL in musculoskeletal trauma patients (e.g., fractures), indicated that pain catastrophizing is a significant predictor of HS/HRQOL five to eight months post-injury [28, 29]. Additionally, some studies focused on the relationship between pain catastrophizing and functional status after DRF [60‐62]. Significant negative relationships were reported between pain catastrophizing and functional status 4 weeks [60] and 3 months after DRF surgery [61] whereas this association was not found in non-operatively treated patients with DRF 6 weeks post-fracture [62]. Our study sample encompassed approximately half DRF and half AF. More than two-third of the patients was non-operatively treated, suggesting that pain catastrophizing is important for QOL in the whole group of patients with either DRF or AF.

A more prominent role for internal PLOC (i.e., significance for all QOL domains and the overall QOL facet) was found compared to external PLOC (i.e., significance for overall, physical, and environmental QOL). Therefore, the belief of being in control of one’s own health seems a powerful cognition with positive relationships with QOL. The direction of this relationship is in agreement with research reporting positive associations between internal HLOC and the level of daily living activities/self-rated health in patients with hip fractures or patients at risk for cardiovascular disease [34, 63]. In contrast to pain catastrophizing and PLOC, patients did not differ on pain coping between QOL classes. We expected a significantly higher variability of pain coping strategies in patients for the trajectories representing higher QOL. However, variability does not directly imply an effective employment of these strategies that may explain the lack of association with QOL. Therefore, this is a limitation of the pain coping subscale that was used [33]. A suggestion might be to incorporate pain coping in further research using a somewhat different approach by examining more specific forms of coping in relation to QOL in patients with fractures (i.e., instead of variability). For example, to examine the suitability of passive versus active coping [30] or possible differences between problem focused, emotional or avoidance coping in relation to QOL [31].

Another possible limitation of our study includes the retrospective measurement of patients’ pre-injury QOL, which may have introduced recall biases. An inflation of pre-injury QOL may occur by re-evaluating pre-injury QOL with reference to the injured status (i.e., response shift). It was found that retrospectively reported pre-injury scores of HS and HRQOL were consistently higher compared to population norms [64]. However, the QOL measurements three, six, and 12 months post-fracture are assumed to be completed with the same internal standard, with reference to the injured status, as Time-0_{retrospective}. Therefore, although the possibility of a small upward bias should be considered, the usage of retrospectively measured pre-injury QOL may be more appropriate than general population norms [64, 65].

Latent class trajectory analysis was used as a technique to gather new insights in complex QOL data of patients with fractures. Therefore, our paper presents a pragmatic application of this statistical taxonomic method. We do not claim that the clusters that were derived present the real theoretical clustering. However, using this taxonomy, we found different QOL trajectories that were defined by several sociodemographic, clinical, and psychological characteristics. These new insights could eventually contribute to the possible identification of patients at risk in clinical practice. The program Latent GOLD and the technique latent class trajectory analysis has already been used in other research areas in a similar pragmatic manner (i.e., as an exploring technique to obtain new insights). For example, in the field of cardiology [66‐68] and perinatology [69]. Latent GOLD produces the most optimal taxonomy based on the data that have been gathered. With a small sample, replication with the use of a new dataset could show a different taxonomy. However, our sample size (n = 543) is relatively large. Therefore, we can be more confident that the results are stable and replicable. The total variance (R ²) explained by our models ranged from 71.6 to 79.4%, which means that individual variation between patients and over time is predicted very well by the classes. In addition, possible bias was taken into account at forehand using the Step 3 method.

This study attempts to encourage clinicians to take a biopsychosocial perspective in the treatment of patients with AF and DRF. Firstly, knowledge of several sociodemographic characteristics of patients is already informative regarding their course of QOL after fracture. However, differentiation is important. In general, the characteristics are different depending on the QOL domain of interest. For example, trajectories of social QOL did only differ significantly on marital and employment status and not on age, sex, or educational level. However, age was significant for overall, physical, psychological, and environmental QOL showing a broad scope of influence. Secondly, results suggested that it is important to be alert towards chronic comorbidities, especially for patients’ physical QOL. The presence of chronic comorbidities seems more crucial than several injury-related clinical variables. Thirdly, this was the first study in patients with DRF and AF including several psychological characteristics, showing that trait anxiety, neuroticism, extraversion, pain catastrophizing, and internal PLOC are significantly different between QOL trajectories (i.e., all QOL domains and the facet). Based on these results, further QOL research is recommended in which psychological predictors (e.g., pain anxiety, general illness beliefs [60, 62, 70]) in addition to sociodemographic and clinical indicators are incorporated. Based on the identified characteristics related to QOL by this study and further research using the biopsychosocial model, patients at risk for low QOL after fracture may be recognized earlier by health care professionals and, therefore, could be better monitored. A more personalized approach can be used, for instance when patients are severely hampered by negative pain beliefs. They may be offered additional care in the form of a psychological intervention aimed to lower pain catastrophizing [71].