Developing a comorbidity score in cancer patients using healthcare utilization databases during the COVID-19 pandemic: An experience from Italy

BACKGROUND

A strong relationship has been observed between comorbidities and the risk of severe/fatal COVID-19 manifestations, but no score is available to evaluate their association in cancer patients. To make up for this lacuna, we aimed to develop a comorbidity score for cancer patients, based on the Lombardy Region healthcare databases.

METHODS

We used hospital discharge records to identify patients with a new diagnosis of solid cancer between February and December 2019; 61 comorbidities were retrieved within 2 years before cancer diagnosis. This cohort was split into training and validation sets. In the training set, we used a LASSO-logistic model to identify comorbidities associated with the risk of developing a severe/fatal form of COVID-19 during the first pandemic wave (March-May 2020). We used a logistic model to estimate comorbidity score weights and then we divided the score into five classes (<=-1, 0, 1, 2-4, >=5). In the validation set, we assessed score performance by areas under the receiver operating characteristic curve (AUC) and calibration plots. We repeated the process on second pandemic wave (October-December 2020) data.

RESULTS

We identified 55,425 patients with an incident solid cancer. We selected 21 comorbidities as independent predictors. The first four score classes showed similar probability of experiencing the outcome (0.2% to 0.5%), while the last showed a probability equal to 5.8%. The score performed well in both the first and second pandemic waves: AUC 0.85 and 0.82, respectively. Our results were robust for major cancer sites too (i.e., colorectal, lung, female breast, and prostate).

CONCLUSIONS

We developed a high performance comorbidity score for cancer patients and COVID-19. Being based on administrative databases, this score will be useful for adjusting for comorbidity confounding in epidemiological studies on COVID-19 and cancer impact.

Health-Related Quality of Life in Older Kidney Transplant Recipients: A National Cohort Study of Short- and Longer-Term Outcomes

Rationale & Objective

Assessing the optimal therapy for older patients (aged ≥65 years) with end-stage kidney disease requires knowledge of longevity and health-related quality of life (HRQoL) outcomes. Kidney transplantation prolongs survival but its long-term impact on HRQoL in older recipients is not well defined. We aimed to prospectively evaluate HRQoL changes from enlisting until 3 years posttransplantation and examine pretransplantation predictors of posttransplantation outcomes.

Study Design

Prospective cohort study.

Setting & Participants

Patients 65 years and older enlisted at the Norwegian National Transplant Center between January 2013 and November 2016.

Predictors

Kidney transplantation, dialysis vintage, and pretransplantation comorbidity assessed using the Liu Comorbidity Index.

Outcomes

HRQoL, assessed using the Kidney Disease Quality of Life Short Form, version 1.3.

Analytical Approach

HRQoL scores obtained at 3 years posttransplantation were compared with those obtained pretransplantation and after 1 year using a paired-sample t test. Multivariable linear mixed-effect models were used to identify possible predictors of HRQoL changes over time.

Results

Among 289 patients included, 220 (mean age, 71.5 years) had undergone transplantation and 136 had completed the 3-year HRQoL follow-up by October 2020. Posttransplant HRQoL, both generic and kidney specific, substantially improved and the benefit persisted for 3 years. For wait-listed candidates remaining on dialysis, HRQoL gradually deteriorated, and recipients who died within 3 years posttransplantation experienced no improvement during the first year. Moderately elevated pretransplantation comorbidity scores and prolonged dialysis vintage independently predicted poor HRQoL outcomes posttransplantation. Recipients receiving dialysis for 1 year or longer with pretransplantation comorbidity scores ≥ 7 experienced a marked and sustained physical deterioration after transplantation.

Limitations

Homogenous and highly selected population.

Conclusions

Transplantation is associated with a sustained HRQoL improvement and should be the preferred treatment for selected older patients. The value of a pretransplant comorbidity score to predict posttransplantation outcomes warrants further evaluation and may improve the selection process.

Development of a specialty intensity score to estimate a patient's need for care coordination across physician specialties

BACKGROUNDS AND AIMS

This article develops a Specialty Intensity Score, which uses patient diagnosis codes to estimate the number of specialist physicians a patient will need to access. Conceptually, the score can serve as a proxy for a patient's need for care coordination across doctors. Such a measure may be valuable to researchers studying care coordination practices for complex patients. In contrast with previous comorbidity scores, which focus primarily on mortality and utilization, this comorbidity score approximates the complexity of a patient's the interaction with the health care system.

METHODS

We use 2015 inpatient claims data from the Centers for Medicare and Medicaid Services to model the relationship between a patient's diagnoses and physician specialty usage. We estimate usage of specialist doctors by using a least absolute shrinkage and selection operator Poisson model. The Specialty Intensity Score is then constructed using this predicted specialty usage. To validate our score, we test its power to predict the occurrence of patient safety incidents and compare that with the predictive power of the Charlson comorbidity index.

RESULTS

Our model uses 127 of the 279 International Classification of Disease, 10th Revision, Clinical Modification (ICD-10-CM) diagnosis subchapters to predict specialty usage, thus creating the Specialty Intensity Score. This score has significantly greater power in predicting patient safety complications than the widely used Charlson comorbidity index.

CONCLUSION

The Specialty Intensity Score developed in this article can be used by health services researchers and administrators to approximate a patient's need for care coordination across multiple specialist doctors. It, therefore, can help with evaluation of care coordination practices by allowing researchers to restrict their analysis of outcomes to the patients most impacted by those practices.

Is venous thromboembolism a predictable marker in older patients with COVID-19 infection? A single-center observational study

Venous thromboembolism (VTE) represents an important clinical complication of patients with SARS-CoV-2 infection, and high plasma D-dimer levels could suggest a higher risk of hypercoagulability. We aimed to analyse if laboratory exams, risk assessment scores, comorbidity scores were useful in predicting the VTE in SARS-CoV-2 patients admitted in internal medicine (IM). We evaluated 49 older adults with suspected VTE analysing history and blood chemistry, besides we calculated the Padua Prediction Score, the modified early warning scoring (MEWS) and the modified Elixhauser index (mEI). All patients underwent venous color-doppler ultrasounds of the lower limbs. Out of the 49 patients enrolled (mean age 79.3±14 years), 10 (20.4%) had deep vein thrombosis (DVT), and they were more frequently female (80% vs 20%, p = 0.04). We could not find any association with the Padua Prediction Score, the MEWS, and the mEI. D-dimer plasma levels were also not associated with DVT. In elderly people hospitalized with SARS-CoV-2 infection hospitalized in IM, our data, although limited by the sample size, suggest that prediction and diagnosis of VTE is difficult, due to lack of precise biomarkers and scores.

Charlson comorbidity index scores and in-hospital prognosis of patients with severe acute respiratory infections

BACKGROUND

Respiratory infections are one of the leading causes of mortality, and comorbid conditions play a significant role in the severity and fatality of these infections.

AIMS

We evaluated the Charlson Comorbidity Index (CCI) score and possible predictors of mortality in hospitalised patients with severe acute respiratory infection (SARI), aiming to test if the CCI is a valid in-hospital prognostic indicator.

METHODS

Patients older than 14 years, hospitalised from 2010 to 2016 due to SARI by viral infection and who were submitted to respiratory virus testing were included. We assessed comorbidity retrospectively through chart review and calculated four variants of the CCI.

RESULTS

Of the 291 patients assessed, 72.8% (n = 212) presented comorbidities, and 24% died (n = 70). The most recurrent comorbidities were chronic pulmonary disease (n = 76/212, 36%) and HIV (n = 50/212, 23.6%). The 1994 age-adjusted CCI predicted in-hospital mortality in SARI patients (P = 0.04), and HIV was associated with in-hospital mortality (P = 0.032).

CONCLUSIONS

The comorbidity scores used to assess mortality risk in hospitalised patients with SARI displayed poor results, but HIV infection was considered a marker of severity. However, other factors should be considered in order to compose a score system that allows us to specifically assess the risk of mortality in patients with SARI.

Validation and Comparison of a Modified Elixhauser Index for Predicting In-Hospital Mortality in Italian Internal Medicine Wards

Purpose

Burden of comorbidities appears to be related to clinical outcomes in hospitalized patients. Clinical stratification of admitted patients could be obtained calculating a comorbidity score, which represents the simplest way to identify the severity of patients' clinical conditions and a practical approach to assess prevalent comorbidities. Our aim was to validate a modified Elixhauser score for predicting in-hospital mortality (IHM) in internal medicine admissions and to compare it with a different one derived from clinical data previously used in a similar setting, having a good prognostic accuracy.

Patients and Methods

A single-center retrospective study enrolled all patients admitted to internal medicine department between January and June 2016. A modified Elixhauser score was calculated from chart review and administrative data; moreover, a second prognostic index was calculated from chart review only. Comorbidity scores were compared using c-statistic.

Results

We analyzed 1614 individuals without selecting the reason for admission, 224 (13.9%) died during hospital stay. Deceased subjects were older (83.3±9.1 vs 78.4±13.5 years; p<0.001) and had higher burden of comorbidities. The modified Elixhauser score calculated by administrative data and by chart review and the comparator one was 18.13±9.36 vs 24.43±11.27 vs 7.63±3.3, respectively, and the c-statistic was 0.758 (95% CI 0.727-0.790), 0.811 (95% CI 0.782-0.840) and 0.740 (95% CI 0.709-0.771), respectively.

Conclusion

The new modified Elixhauser score showed a similar performance to a previous clinical prognostic index when it was calculated using administrative data; however, its performance improved if calculation was based on chart review.

Development of comorbidity score for patients undergoing major surgery

OBJECTIVE

To develop and validate a claims-based comorbidity score for patients undergoing major surgery, and compare its performance with established comorbidity scores.

DATA SOURCE

Five percent Medicare data from 2007 to 2014.

STUDY DESIGN

Retrospective cohort study of patients aged ≥65 years undergoing six major operations (N = 99 250).

DATA COLLECTION

One-year mortality was the primary outcome. Secondary outcomes were hospital mortality, 30-day mortality, 30-day readmission, and length of stay. The comorbidity score was developed in the derivation cohort (70 percent sample) using logistic regression model. The comorbidity score was calibrated and validated in the validation cohort (30 percent sample), and compared against the Charlson, Elixhauser, and Centers for Medicare and Medicaid Services Hierarchical Condition Categories (CMS-HCC) comorbidity scores using c-statistic, net reclassification improvement, and integrated discrimination improvement.

PRINCIPAL FINDINGS

In the validation cohort, the surgery-specific comorbidity score was well calibrated and performed better than the Charlson, Elixhauser, and CMS-HCC comorbidity scores for all outcomes; the performance was comparable to the CMS-HCC for 30-day readmission. For example, the surgery-specific comorbidity score (c-statistic = 0.792; 95% CI, 0.785-0.799) had greater discrimination than the Charlson (c-statistic = 0.747; 95% CI, 0.739-0.755), Elixhauser (c-statistic = 0.747; 95% CI, 0.735-0.755), or CMS-HCC (c-statistic = 0.755; 95% CI, 0.747-0.763) scores in predicting 1-year mortality. The net reclassification improvement and integrated discrimination improvement were greater for surgery-specific comorbidity score compared to the Charlson, Elixhauser, and CMS-HCC scores.

CONCLUSIONS

Compared to commonly used comorbidity measures, a surgery-specific comorbidity score better predicted outcomes in the surgical population.

Predicting 90-Day Mortality in Locoregionally Advanced Head and Neck Squamous Cell Carcinoma after Curative Surgery

Purpose: To propose a risk classification scheme for locoregionally advanced (Stages III and IV) head and neck squamous cell carcinoma (LA-HNSCC) by using the Wu comorbidity score (WCS) to quantify the risk of curative surgeries, including tumor resection and radical neck dissection. Methods: This study included 55,080 patients with LA-HNSCC receiving curative surgery between 2006 and 2015 who were identified from the Taiwan Cancer Registry database; the patients were classified into two groups, mortality (n = 1287, mortality rate = 2.34%) and survival (n = 53,793, survival rate = 97.66%), according to the event of mortality within 90 days of surgery. Significant risk factors for mortality were identified using a stepwise multivariate Cox proportional hazards model. The WCS was calculated using the relative risk of each risk factor. The accuracy of the WCS was assessed using mortality rates in different risk strata. Results: Fifteen comorbidities significantly increased mortality risk after curative surgery. The patients were divided into low-risk (WCS, 0–6; 90-day mortality rate, 0–1.57%), intermediate-risk (7–11; 2.71–9.99%), high-risk (12–16; 17.30–20.00%), and very-high-risk (17–18 and >18; 46.15–50.00%) strata. The 90-day survival rates were 98.97, 95.85, 81.20, and 53.13% in the low-, intermediate-, high-, and very-high-risk patients, respectively (log-rank p < 0.0001). The five-year overall survival rates after surgery were 70.86, 48.62, 22.99, and 18.75% in the low-, intermediate-, high-, and very-high-risk patients, respectively (log-rank p < 0.0001). Conclusion: The WCS is an accurate tool for assessing curative-surgery-related 90-day mortality risk and overall survival in patients with LA-HNSCC.

Can We Predict Morbidity and Mortality of Patients Aged 75 Years and Older Undergoing Cystectomy?

Radical cystectomy is associated with a high postoperative mortality and morbidity in older patients. We aimed to define the predictive value of comorbidity scores and determine the prognostic factors of postoperative complications. Preoperative associated morbidities were collected and graded according to the American Society of Anesthesiologists (ASA) score system, the Adult Comorbidity Evaluation (ACE) scale and the Charlson comorbidity index. Surgical complications were graded according to Clavien classification. Early and late complications were recorded. Data are from 49 consecutive patients aged ≥ 75 years who had an open surgery for bladder cancer. The most commonly associated conditions were smoking, renal insufficiency, and arterial hypertension. Incidence of early and late complications was 49% and 16%, respectively. Four and 25 death events occurred during the early and late follow-up, respectively. The incidence of morbidity and mortality were not related to ASA, ACE or Charlson scores. Preoperative malnutrition, renal insufficiency, higher need of perioperative blood transfusions, and prolonged ileus were identified as risk factors of postoperative morbidity. Late complications seemed related to low weight.