Modified-Chronic Disease Score (M-CDS): Predicting the individual risk of death using drug prescriptions

Utility of prescription-based comorbidity indices for predicting mortality among Australian men with prostate cancer

BACKGROUND

Drug prescription registries has become an alternative data source to hospital admission databases for measuring comorbidities. However, the predictive validity of prescription-based comorbidity measures varies based on the population under investigation and outcome of interest. We aimed to determine which prescription-based index of comorbidity has most utility in Australian men with prostate cancer.

METHODS

We studied 25,414 South Australian men diagnosed with prostate cancer between 2003 and 2019 from state-wide administrative linked datasets. The Rx-Risk index, Chronic Disease Score (CDS), Drug Comorbidity Index (DCI) and Pharmaceutical Prescribing Profile (P3) with one year lookback period from prostate cancer diagnosis were evaluated. The predictive ability of each index to determine all-cause deaths within two and five years of prostate cancer diagnosis was compared using the c-statistic from flexible parametric survival models, adjusting for age, socioeconomic status and year of prostate cancer diagnosis.

RESULTS

The Rx-Risk index performed better in predicting two-year (c-statistic = 0.818) and five-year (c-statistic = 0.784) all-cause mortality than P3, CDS and DCI. Including comorbidity measures as continuous scores resulted in a better performance than including them as categories. Grouping scores into four categories (≤0, >0 - ≤1, >1 - ≤2, and >2) resulted in better performance and calibration than using fewer categories.

CONCLUSION

Rx-Risk was validated in Australia and reflects Australian prescribing patterns. It showed better predictive performance for mortality in our study, with a modest improvement over P3, CDS and DCI. For research with prostate cancer populations, we recommend the use of drug-based comorbidity indices that have been validated in a similar population.

Identifying patient subgroups with different trends of patient-reported outcomes (PROMs) after elective knee arthroplasty

BACKGROUND

Patient-reported outcome measures (PROMs) are increasingly being used to assess the effectiveness of elective total knee arthroplasty (TKA). However, little is known about how PROMs scores change over time in these patients. The aim of this study was to identify the trajectories of quality of life and joint functioning, and their associated demographic and clinical features in patients undergoing elective TKA.

METHODS

A prospective, cohort study was conducted, in which PROMs questionnaires (Euro Quality 5 Dimensions 3L, EQ-5D-3L, and Knee injury and Osteoarthritis Outcome Score Patient Satisfaction, KOOS-PS) were administered to patients at a single center undergoing elective TKA before surgery, and at 6 and 12 months after surgery. Latent class growth mixture models were used to analyze the patterns of change in PROMs scores over time. Multinomial logistic regression was used to investigate the association between patient characteristics and PROMs trajectories.

RESULTS

A total of 564 patients were included in the study. The analysis highlighted differential patterns of improvement after TKA. Three distinct PROMs trajectories were identified for each PROMs questionnaire, with one trajectory indicating the most favorable outcome. Female gender appears to be associated with a presentation to surgery with worse perceived quality of life and joint function than males, but also more rapid improvement after surgery. Having an ASA score greater than 3 is instead associated with a worse functional recovery after TKA.

CONCLUSION

The results suggest three main PROMs trajectories in patients undergoing elective TKA. Most patients reported improved quality of life and joint functioning at 6 months, which then stabilized. However, other subgroups showed more varied trajectories. Further research is needed to confirm these findings and to explore the potential clinical implications of these results.

Patient reported outcomes measures (PROMs) trajectories after elective hip arthroplasty: a latent class and growth mixture analysis

Background

Patient-reported outcome measures (PROMs) are an extensively used tool to assess and improve the quality of healthcare services. PROMs can be related to individual demographic and clinical characteristics in patients undergoing hip arthroplasty (HA). The aim of this study is to identify distinct subgroups of patients with unique trajectories of PROMS scores and to determine patients’ features associated with these subgroups.

Methods

We conducted a prospective, cohort study in which PROMs questionnaires (Euro Quality 5 Dimensions 3L, EQ-5D-3L, Euro-Quality-Visual-Analytic-Score, EQ-VAS, Hip disability and Osteoarthritis Outcome Score, HOOS-PS) were administered to patients undergoing elective HA pre-operatively, and at 6 and 12 months after surgery. For each measure, latent class growth analysis and growth mixture models were used to identify subgroups of patients with distinct trajectories of scores. Demografic and clinical predictors of the latent classes in growth mixture model were identified using a 3-step approach.

Results

We found three distinct trajectories for each PROM score. These trajectories indicated a response heterogeneity to the HA among the patients (n = 991). Patient’s gender, ASA score, and obesity were significantly associated with different PROMs trajectories.

Conclusions

We identified three distinct trajectories for each of the three PROMs indicators. Several demographic and clinical characteristics are associated with the different trajectories of PROMs at 6 and 12 months after HA and could be used to identify groups of patients with different outcomes following HA surgery. These findings underline the importance of patient-centered care, supporting the usefulness of integrating PROMs data alongside routinely collected healthcare records for guiding clinical care and maximizing patients’ positive outcomes.

Trial registration: Protocol version (1.0) and trial registration data are available on the platform www.clinicaltrial.gov with the identifier NCT03790267, posted on December 31, 2018.

Supplementary Information

The online version contains supplementary material available at 10.1186/s41687-022-00503-5.

Variations of the quality of care during the COVID-19 pandemic affected the mortality rate of non-COVID-19 patients with hip fracture

Introduction

As COVID-19 roared through the world, governments worldwide enforced containment measures that affected various treatment pathways, including those for hip fractures (HFs). This study aimed to measure process and outcome indicators related to the quality of care provided to non-COVID-19 elderly patients affected by HF in Emilia-Romagna, a region of Italy severely hit by the pandemic.

Methods

We collected the hospital discharge records of all patients admitted to the hospitals of Emilia-Romagna with a diagnosis of HF from January to May in the years 2019 (pre-pandemic period) and 2020 (pandemic period). We analyzed surgery rate, surgery delays, length of hospital stay, timely rehabilitation, and 30-day mortality for each HF patient. We evaluated monthly data (2020 vs. 2019) with the chi-square and t-test, where appropriate. Logistic regression was used to investigate the differences in 30-day mortality.

Results

Our study included 5379 patients with HF. In April and May 2020, there was a significant increase in the proportion of HF patients that did not undergo timely surgery. In March 2020, we found a significant increase in mortality (OR = 2.22). Male sex (OR = 1.92), age ≥90 years (OR = 4.33), surgery after 48 hours (OR = 3.08) and not receiving surgery (OR = 6.19) were significantly associated with increased mortality. After adjusting for the aforementioned factors, patients hospitalized in March 2020 still suffered higher mortality (OR = 2.21).

Conclusions

There was a reduction in the overall quality of care provided to non-COVID-19 elderly patients affected by HF, whose mortality increased in March 2020. Patients’ characteristics and variations in processes of care partially explained this increase. Policymakers and professionals involved in the management of COVID-19 patients should be aware of the needs of patients with other health needs, which should be carefully investigated and included in future emergency preparedness and response plans.

Komorbidität bei Pemphigus: eine Fall-Kontroll-Studie

HINTERGRUND UND ZIELE

Pemphigus ist mit physischen und psychischen Erkrankungen assoziiert. Diese Studie soll derartige Zusammenhänge bei Patienten mit Pemphigus näher untersuchen sowie die Komorbidität nach Geschlecht, Alter, dem Pemphigus Disease Area Index, der Diagnoseverzögerung und der Beteiligung von Haut/Schleimhaut analysieren.

PATIENTEN UND METHODEN

Jedem Pemphigus-Patienten wurden acht Kontrollen mit ähnlichem Alter, Geschlecht und Wohnsitz zugeordnet. Die Wahrscheinlichkeit für Begleiterkrankungen bei Patienten und Kontrollpersonen wurde anhand univariater konditionaler Regressionsmodelle bestimmt. Begleiterkrankungen, die in den univariaten Modellen mit P < 0,05 mit der Diagnose Pemphigus assoziiert waren, wurden dann in einem Vorwärtsverfahren in ein multivariates konditionales Regressionsmodell eingefügt.

ERGEBNISSE

Die Studie umfasste 163 Patienten mit Pemphigus. Die hauptsächlichen Erkrankungen zum Diagnosezeitpunkt waren kardiovaskuläre Erkrankungen, Hyperlipidämie, Autoimmunerkrankungen der Schilddrüse, autoimmune/entzündliche Dermatosen und Krebs. In der multivariaten konditionalen Regressionsanalyse waren Krebs und autoimmune/entzündliche Dermatosen unabhängig mit Pemphigus assoziiert. In Sensitivitätsanalysen, in denen vier Patienten mit paraneoplastischem Pemphigus ausgeschlossen wurden, waren diese Assoziationen ebenfalls signifikant.

SCHLUSSFOLGERUNGEN

Krebs und autoimmune/entzündliche Dermatosen sind möglicherweise auslösende Faktoren für Pemphigus dar und sollten als frühe Warnsignale für diese Erkrankung angesehen werden.

Comorbid diseases associated with pemphigus: a case-control study

BACKGROUND AND OBJECTIVES

Pemphigus has been associated with physical and psychiatric comorbid diseases. This study aims to further investigate these associations in patients with pemphigus, and to analyze the relationships of comorbid conditions with sex and age, pemphigus disease area index score, diagnostic delay and cutaneous/mucous involvement.

PATIENTS AND METHODS

Patients with pemphigus were matched by age, gender and area of residence with eight controls each. The odds of comorbid conditions in patients vs. matched controls was determined using univariate conditional logistic regression models. Comorbid diseases significantly associated with the diagnosis of pemphigus at P < 0.05 in univariate models were subsequently included in a multivariable conditional logistic regression model with a forward procedure.

RESULTS

The study sample included 163 patients with pemphigus. Cardiovascular diseases, hyperlipidemia, autoimmune thyroid disorders, dermatological autoimmune/inflammatory conditions and cancer were the most prominent conditions at the time of diagnosis. In the multiple conditional regression analysis, the two diagnoses independently associated with patients with pemphigus were cancer and dermatological autoimmune/inflammatory conditions. In sensitivity analyses excluding four patients with paraneoplastic pemphigus, these associations were still significant.

CONCLUSIONS

Cancer and dermatological autoimmune/inflammatory conditions may represent possible triggering conditions for pemphigus and should be considered as early warning signs for the disease.

A narrative review of using prescription drug databases for comorbidity adjustment: A less effective remedy or a prescription for improved model fit?

BACKGROUND

The use of claims data for identifying comorbid conditions in patients for research purposes has been widely explored. Traditional measures of comorbid adjustment included diagnostic data (e.g., ICD-9-CM or ICD-10-CM codes), with the Charlson and Elixhauser methodology being the two most common approaches. Prescription data has also been explored for use in comorbidity adjustment, however early methodologies were disappointing when compared to diagnostic measures.

OBJECTIVE

The objective of this methodological review is to compare results from newer studies using prescription-based data with more traditional diagnostic measures.

METHODS

A review of studies found on PubMed, Medline, Embase or CINAHL published between January 1990 and December 2020 using prescription data for comorbidity adjustment. A total of 50 studies using prescription drug measures for comorbidity adjustment were found.

CONCLUSIONS

Newer prescription-based measures show promise fitting models, as measured by predictive ability, for research, especially when the primary outcomes are utilization or drug expenditure rather than diagnostic measures. More traditional diagnostic-based measures still appear most appropriate if the primary outcome is mortality or inpatient readmissions.