Identifying multiple myeloma patients using data from the French health insurance databases: Validation using a cancer registry

Validated administrative data based ICD-10 algorithms for chronic conditions: A systematic review

OBJECTIVE

This systematic review aimed to identify ICD-10 based validated algorithms for chronic conditions using health administrative data.

METHODS

A comprehensive systematic literature search using Ovid MEDLINE, Embase, PsycINFO, Web of Science and CINAHL was performed to identify studies, published between 1983 and May 2023, on validated algorithms for chronic conditions using administrative health data. Two reviewers independently screened titles and abstracts and reviewed full text of selected studies to complete data extraction. A third reviewer resolved conflicts arising at the screening or study selection stages. The primary outcome was validated studies of ICD-10 based algorithms with both sensitivity and PPV of ≥70 %. Studies with either sensitivity or PPV <70 % were included as secondary outcomes.

RESULTS

Overall, the search identified 1686 studies of which 54 met the inclusion criteria. Combining a previously published literature search, a total of 61 studies were included for data extraction. The study identified 40 chronic conditions with high validity and 22 conditions with moderate validity. The validated algorithms were based on administrative data from different countries including Canada, USA, Australia, Japan, France, South Korea, and Taiwan. The algorithms identified included several types of cancers, cardiovascular conditions, kidney diseases, gastrointestinal disorders, and peripheral vascular diseases, amongst others.

CONCLUSION

With ICD-10 prominently used across the world, this up-to-date systematic review can prove to be a helpful resource for research and surveillance initiatives using administrative health data for identifying chronic conditions.

The Singular Epidemiology of Plasmacytoma and Multiple Myeloma in French Guiana

BACKGROUND

The objective was to review a decade of plasmacytoma (PC) and multiple myeloma (MM) data from French Guiana, and to study its spatial and temporal trends.

METHODS

This was a retrospective study of MM and PC between January 2005 and December 2014 using cancer registry data, including age-standardized incidence and mortality rates.

RESULTS

There were 110 cases of PC and MM (62 women and 48 men), representing the eighth most frequent malignancy in French Guiana. PC and MM were much more common in females. In men, 79% of cases occurred at ≥55 years, and in women, 90% of cases occurred at ≥50 years. The median age at diagnosis was 60 years for men and 66 years for women, while it was 72 years for men and 75 years for women in mainland France. The incidence rate standardized to the world population was 5.9 patients of PC and MM per 100,000 men/year and 7.8 per 100,000 women/year.

CONCLUSIONS

In our territory, the incidence of PC and MM was higher and patients were diagnosed at a substantially younger age than in mainland France. Women had a greater incidence than men, and there was an increasing temporal trend of incidence among women. African ancestry and the frequency of obesity, notably among women, could have contributed to this observation.

Drug-drug interactions of protein kinase inhibitors in chronic myeloid leukaemia patients: A study using the French health insurance database

The introduction of protein kinase inhibitors (PKIs) for chronic myeloid leukaemia (CML) has considerably improved prognosis of the disease but has also demonstrated a great potential for drug-drug interactions. Using the French health insurance databases, we aim to investigate the frequency, identify the associated factors and describe the potential consequences of potential drug-drug interactions (pPKI-DIs) between PKIs and concurrent medications in CML. A retrospective cohort study has been performed among patients with CML identified in the French healthcare database from 2011 to 2014. A pPKI-DI is defined as the presence of drugs listed as 'interacting' on the same day as PKI dispensing (co-dispensing) or in its coverage period (co-medication) during the first year of follow-up. The list of interacting drugs is based on the summary of products characteristics (SPCs) and Thesaurus of interactions. We performed specific nested case-control comparisons to investigate the association between PKI-DI and each of the three potential outcomes (death, hospitalisation for adverse drug reactions and switch to another PKI). We included 3480 patients; 1429 (41%) had a co-dispensing pPKI-DI, and 2153 (62%) had a co-medication pPKI-DI; 50% of the pPKI-DIs were 'to be taken into account', and 17% were 'not recommended'. The PKI with the most interactions was imatinib, and additional common drug classes included statins, benzodiazepines and proton pump inhibitors. Multivariate analysis demonstrated that the use of a higher number of additional drugs, comorbidities at baseline, high number of prescribers and higher ages were potential risk factors. Nilotinib and dasatinib showed a tendency towards a higher risk of pPKI-DI compared to imatinib. Despite the fact that some PKI-DIs were potentially clinically relevant, we did not find any significant association with death, hospitalisation for adverse drug reactions and switching. These findings should increase awareness to help reduce the prevalence of PKI-drug interactions and thereby ensure better management of CML patients.

Assessing the treatment pattern, health care resource utilisation, and economic burden of multiple myeloma in France using the Système National des Données de Santé (SNDS) database: a retrospective cohort study

BACKGROUND

Real-world data on health care resource utilisation (HCRU) and costs for French patients with multiple myeloma (MM) are limited due to the quickly evolving MM treatment landscape. This retrospective, national-level study quantified the MM economic burden in France.

METHODS

The study included patients with newly diagnosed MM from the Système National des Données de Santé coverage claims database between 2013 and 2018 who received active treatment within 30 days of diagnosis. HCRU included hospitalisations, drugs, consultations, procedures, tests, devices, transport, and sick leave. Costs were annualized to 2019 prices. Drug treatments, reported by line of therapy (LOT), were algorithmically defined using drug regimen, duration of therapy, and gaps between treatments. Analyses were stratified by stem cell transplantation status and LOT.

RESULTS

Among 6413 eligible patients, 6229 (97.1%) received ≥ 1 identifiable LOT; most received 1 (39.8%) or 2 LOT (27.5%) during follow-up. Average annual hospitalisation was 6.3 episodes/patient/year (median duration: 11.6 days). The average annual cost/patient was €58.3 K. Key cost drivers were treatment (€28.2 K; 39.5% of total HCRU within one year of MM diagnosis) and hospitalisations (€22.2 K; 48.6% of total HCRU costs in first year). Monthly treatment-related costs increased from LOT1 (€2.447 K) and LOT5 + (€7.026 K); only 9% of patients received LOT5 + . At LOT4 + , 37 distinct regimens were identified. Hospitalisation costs were higher in patients with stem cell transplantation than total population, particularly in the first year.

CONCLUSIONS

This study showed a high economic burden of MM in France (€72.37 K/patient/year in the first year) and the diversity of regimens used in late-line treatments.

Use of a hospital administrative database to identify and characterize community-acquired, hospital-acquired and drug-induced acute kidney injury

BACKGROUND

Acute kidney injury (AKI) has serious short- and long-term consequences. The objective of the present study of a cohort of hospitalized patients with AKI was to (i) evaluate the proportion of patients with hospital-acquired (HA) AKI and community-acquired (CA) AKI, the characteristics of these patients and the AKIs, and the short-term outcomes, and (ii) determine the performance of several ICD-10 codes for identifying AKI (both CA and HA) and drug-induced AKI.

METHODS

A cohort of hospitalized patients with AKI was constituted by screening hospital's electronic medical records (EMRs) for cases of AKI. We distinguished between and compared CA-AKI and HA-AKI and evaluated the proportion of AKIs that were drug-induced. The EMR data were merged with hospital billing codes (according to the International Classification of Diseases, 10th Edition (ICD-10)) for each hospital stay. The ability of ICD-10 codes to identify AKIs (depending on the type of injury) was determined by calculating the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). Lastly, we sought to validate specific ICD-10 codes for drug-induced AKI.

RESULTS

Of the 2473 patients included, 1557 experienced an AKI (HA-AKI: 59.3%; CA-AKI: 40.7%). Patients with CA-AKI had a better short-term outcome and a lower death rate (7.6%, vs. 20% for HA-AKI). One AKI in three was drug-induced. The combination of AKI codes had a very high specificity (94.8%), a high PPV (94.9%), a moderate NPV (56.7%) and moderate sensitivity (57.4%). The sensitivity was higher for CA-AKI (72.2%, vs. 47.2% for HA-AKI), for more severe AKI (82.8% for grade 3 AKI vs. 43.7% for grade 1 AKI), and for patients with CKD. Use of a specific ICD-10 code for drug-induced AKI (N14x) alone gave a very low sensitivity (1.8%), whereas combining codes for adverse drug reactions with AKI-specific codes increased the sensitivity.

CONCLUSION

Our results show that the combination of an EMR-based analysis with ICD-10-based hospital billing codes gives a comprehensive "real-life" picture of AKI in hospital settings. We expect that this approach will enable researchers to study AKI in more depth.

Development and Validation of a Model to Identify Alzheimer's Disease and Related Syndromes in Administrative Data

BACKGROUND

Administrative data are used in the field of Alzheimer's Disease and Related Syndromes (ADRS), however their performance to identify ADRS is unknown.

OBJECTIVE

i) To develop and validate a model to identify ADRS prevalent cases in French administrative data (SNDS), ii) to identify factors associated with false negatives.

METHODS

Retrospective cohort of subjects ≥ 65 years, living in South-Western France, who attended a memory clinic between April and December 2013. Gold standard for ADRS diagnosis was the memory clinic specialized diagnosis. Memory clinics' data were matched to administrative data (drug reimbursements, diagnoses during hospitalizations, registration with costly chronic conditions). Prediction models were developed for 1-year and 3-year periods of administrative data using multivariable logistic regression models. Overall model performance, discrimination, and calibration were estimated and corrected for optimism by resampling. Youden index was used to define ADRS positivity and to estimate sensitivity, specificity, positive predictive and negative probabilities. Factors associated with false negatives were identified using multivariable logistic regressions.

RESULTS

3360 subjects were studied, 52% diagnosed with ADRS by memory clinics. Prediction model based on age, all-cause hospitalization, registration with ADRS as a chronic condition, number of anti-dementia drugs, mention of ADRS during hospitalizations had good discriminative performance (c-statistic: 0.814, sensitivity: 76.0%, specificity: 74.2% for 2013 data). 419 false negatives (24.0%) were younger, had more often ADRS types other than Alzheimer's disease, moderate forms of ADRS, recent diagnosis, and suffered from other comorbidities than true positives.

CONCLUSION

Administrative data presented acceptable performance for detecting ADRS. External validation studies should be encouraged.

Intra-database validation of case-identifying algorithms using reconstituted electronic health records from healthcare claims data

BACKGROUND

Diagnosis performances of case-identifying algorithms developed in healthcare database are usually assessed by comparing identified cases with an external data source. When this is not feasible, intra-database validation can present an appropriate alternative.

OBJECTIVES

To illustrate through two practical examples how to perform intra-database validations of case-identifying algorithms using reconstituted Electronic Health Records (rEHRs).

METHODS

Patients with 1) multiple sclerosis (MS) relapses and 2) metastatic castration-resistant prostate cancer (mCRPC) were identified in the French nationwide healthcare database (SNDS) using two case-identifying algorithms. A validation study was then conducted to estimate diagnostic performances of these algorithms through the calculation of their positive predictive value (PPV) and negative predictive value (NPV). To that end, anonymized rEHRs were generated based on the overall information captured in the SNDS over time (e.g. procedure, hospital stays, drug dispensing, medical visits) for a random selection of patients identified as cases or non-cases according to the predefined algorithms. For each disease, an independent validation committee reviewed the rEHRs of 100 cases and 100 non-cases in order to adjudicate on the status of the selected patients (true case/ true non-case), blinded with respect to the result of the corresponding algorithm.

RESULTS

Algorithm for relapses identification in MS showed a 95% PPV and 100% NPV. Algorithm for mCRPC identification showed a 97% PPV and 99% NPV.

CONCLUSION

The use of rEHRs to conduct an intra-database validation appears to be a valuable tool to estimate the performances of a case-identifying algorithm and assess its validity, in the absence of alternative.

Vaccination during the First Diagnosis of Multiple Myeloma: A Cohort Study of the French National Health Insurance Database

Purpose: Infections are frequent and often result in serious complications in patients with multiple myeloma (MM). Prophylactic vaccination is recommended for influenza virus, Streptococcus pneumoniae (SP), and Hemophilus influenzaeb (Hib). The aims of this study were to measure the vaccination rates within 24 months after the diagnosis of multiple myeloma and to identify factors associated with vaccine use. Methods: MM patients were selected through the French national health insurance database from 1 January 2010 to 31 December 2015. Patients with a previous history of MM were excluded. Results: Vaccination rates against influenza, SP, and Hib among 22,831 newly diagnosed MM patients were, respectively, 28.5%, 10.3%, and 1.4%. Only 0.7% received all three vaccines. Factors associated with vaccination were young age, male gender, an absence of comorbidity, a history of higher medication and vaccine consumption, Herpes simplex virus (HSV), Varicella zoster virus (VZV), and the use of pneumocystis prophylaxis. Conclusion: The low rates of vaccination indicate the need to improve physician and MM patient adherence and education regarding vaccination.

The challenges of pharmacoepidemiology of orphan drugs in rare diseases

Large electronic health records database available at a national level offer great opportunity for research in rare diseases and orphan drugs. Methods and data used in pharmacoepidemiology present a great potential for epidemiology, drug utilization studies, drug safety, drug effectiveness and pharmacoeconomics. This review presents the different sources of data in Europe, with a special focus on the French situation, with the recent implementation of SNDS (système national des données de santé [French national health data wharehouse]). Some examples are given. Development of rigorous and innovative methods must be encouraged in the future.

Multiple myeloma with primary amyloidosis presenting with digestive symptoms: A case report and literature review

We present a case of multiple myeloma with primary systemic amyloidosis presenting with digestive symptoms in a 32-year-old male. Initial symptoms included upper abdominal discomfort for 4 months, and stool with mucous and blood for 1 month. Erosive gastritis, Helicobacter pylori infection, haematochezia, and weight loss were noted, but without bone pain, anaemia, or hypercalcaemia. Bone marrow examination showed 18.5% mature monoclonal plasma cells that were λ light chain protein and CD38 positive. Three courses of 28-day PTD therapy (i.e., bortezomib, dexamethasone, and thalidomide) were administered. Gastrointestinal symptoms and laboratory parameters improved. Post-treatment follow-up showed 0.5% plasma cells with normal morphology in bone marrow, urine λ light chain 10.1 mg/L, and negative M protein. Nevertheless, the patient died of multiple organ system failure 8 months after treatment. CONCLUSIONS: Amyloidosis is an uncommon finding in patients with multiple myeloma, especially in younger individuals.

Validating an algorithm for multiple myeloma based on administrative data using a SEER tumor registry and medical record review

PURPOSE

Large numbers of multiple myeloma patients can be studied in real-world clinical settings using administrative databases. The validity of these studies is contingent upon accurate case identification. Our objective was to develop and evaluate algorithms to use with administrative data to identify multiple myeloma cases.

METHODS

Patients aged ≥18 years with ≥1 International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) code for multiple myeloma (203.0x) were identified at two study sites. At site 1, several algorithms were developed and validated by comparing results to tumor registry cases. An algorithm with a reasonable positive predictive value (PPV) (0.81) and sensitivity (0.73) was selected and then validated at site 2 where results were compared with medical chart data. The algorithm required that ICD-9-CM codes 203.0x occur before and after the diagnostic procedure codes for multiple myeloma.

RESULTS

At site 1, we identified 1432 patients. The PPVs of algorithms tested ranged from 0.54 to 0.88. Sensitivities ranged from 0.30 to 0.88. At site 2, a random sample (n = 400) was selected from 3866 patients, and medical charts were reviewed by a clinician for 105 patients. Algorithm PPV was 0.86 (95% CI, 0.79-0.92).

CONCLUSIONS

We identified cases of multiple myeloma with adequate validity for claims database analyses. At least two ICD-9-CM diagnosis codes 203.0x preceding diagnostic procedure codes for multiple myeloma followed by ICD-9-CM codes within a specific time window after diagnostic procedure codes were required to achieve reasonable algorithm performance.

Cancer recording in patients with and without type 2 diabetes in the Clinical Practice Research Datalink primary care data and linked hospital admission data: a cohort study

OBJECTIVES AND SETTING

Conflicting results from studies using electronic health records to evaluate the associations between type 2 diabetes and cancer fuel concerns regarding potential biases. This study aimed to describe completeness of cancer recording in UK primary care data linked to hospital admissions records.

DESIGN

Patients aged 40+ years with insulin or oral antidiabetic prescriptions in Clinical Practice Research Datalink (CPRD) primary care without type 1 diabetes were matched by age, sex and general practitioner practice to non-diabetics. Those eligible for linkage to Hospital Episode Statistics Admitted Patient Care (HES APC), and with follow-up during April 1997-December 2006 were included.

PRIMARY AND SECONDARY OUTCOME MEASURES

Cancer recording and date of first record of cancer were compared. Characteristics of patients with cancer most likely to have the diagnosis recorded only in a single data source were assessed. Relative rates of cancer estimated from the two datasets were compared.

PARTICIPANTS

53 585 patients with type 2 diabetes matched to 47 435 patients without diabetes were included.

RESULTS

Of all cancers (excluding non-melanoma skin cancer) recorded in CPRD, 83% were recorded in HES APC. 94% of cases in HES APC were recorded in CPRD. Concordance was lower when restricted to same-site cancer records, and was negatively associated with increasing age. Relative rates for cancer were similar in both datasets.

CONCLUSIONS

Good concordance in cancer recording was found between CPRD and HES APC among type 2 diabetics and matched controls. Linked data may reduce misclassification and increase case ascertainment when analysis focuses on site-specific cancers.

Real life management of patients hospitalized with multiple myeloma in France

Background

Patients with multiple myeloma included in prospective clinical trials are highly selected and therefore are expected not to be representative of the entire patient population. Additionally recommendations based on literature data and randomized trials are not systematically implemented in all patients. We sought to determine how patients hospitalized with a diagnosis of multiple myeloma are currently treated in France.

Methods and findings

We performed a nation-wide search using the Programme de Médicalisation des Systèmes d’Information (PMSI) database which includes anonymous data for all patients hospitalized in France. We identified newly diagnosed cases in 2012 and analyzed the number and duration of hospital stays, coexisting conditions and treatment modalities with data available until the end of 2015. A diagnosis of multiple myeloma was determined for the first time during a hospitalization in France in 2012 in 6,282 patients (3,234 males and 3,048 females). The median age at diagnosis was 74 years (72 in males and 76 in females). A majority (55.3%) of patients were diagnosed and treated in a single heath center, including 37% in a university hospital and 52% in a non-university public hospital. Comorbidities potentially impacting on myeloma treatment were present in 57.5% of patients at diagnosis, and 15% had an associated diagnosis of another neoplasia. Intensive therapies with stem cell transplants were performed in 1033 patients (16% of total), the majority of which were aged less than 65 (881 patients, 85.3%). Stem cell transplants were performed more frequently in males while the distance between the site of residence and the transplant center had no impact on likelihood of receiving a transplant. Only 60% of patients less than 65 years old who were treated for their disease underwent intensification with stem cell transplant within the 4-year follow-up period.

Conclusions

A large majority of patients hospitalized with a diagnosis of multiple myeloma are elderly, in particular females, and not eligible for transplants. Among the patients aged less than 65 and receiving therapy for their disease, 40% do not undergo transplants. These data emphasize the need for alternative therapies.

A novel approach for medical research on lymphomas: A study validation of claims-based algorithms to identify incident cases

The use of claims database to study lymphomas in real-life conditions is a crucial issue in the future. In this way, it is essential to develop validated algorithms for the identification of lymphomas in these databases. The aim of this study was to assess the validity of diagnosis codes in the French health insurance database to identify incident cases of lymphomas according to results of a regional cancer registry, as the gold standard.Between 2010 and 2013, incident lymphomas were identified in hospital data through 2 algorithms of selection. The results of the identification process and characteristics of incident lymphomas cases were compared with data from the Tarn Cancer Registry. Each algorithm's performance was assessed by estimating sensitivity, predictive positive value, specificity (SPE), and negative predictive value.During the period, the registry recorded 476 incident cases of lymphomas, of which 52 were Hodgkin lymphomas and 424 non-Hodgkin lymphomas. For corresponding area and period, algorithm 1 provides a number of incident cases close to the Registry, whereas algorithm 2 overestimated the number of incident cases by approximately 30%. Both algorithms were highly specific (SPE = 99.9%) but moderately sensitive. The comparative analysis illustrates that similar distribution and characteristics are observed in both sources.Given these findings, the use of claims database can be consider as a pertinent and powerful tool to conduct medico-economic or pharmacoepidemiological studies in lymphomas.

Identifying cancer drug regimens in French health insurance database: An application in multiple myeloma patients

PURPOSE

There is no consensus on how to handle complex drug combinations of cancer drugs through medico-administrative databases. Our objective was to develop an algorithm for identifying the nature and patterns of treatment lines in a cohort of newly treated multiple myeloma patients.

METHODS

A cohort of multiple myeloma patients starting a first treatment line was built using both ambulatory and hospital data from regional data of the French national healthcare system database (SNIIRAM). Patients were identified from January 2011 to September 2013 using ICD-10 codes for multiple myeloma ('C90') within long-term conditions or diagnosis from hospital data. Drugs of interest for cycle identification included bortezomib, imids (thalidomide, lenalidomide), alkylating drugs (cyclophosphamide, melphalan, bendamustine, doxorubicin) and dexamethasone. An algorithm was applied to define combinations of treatment received in the first 6 months of treatment.

RESULTS

Among the 236 patients included, 45% received bortezomib-melphalan-prednisone (VMP: n = 107), 22% bortezomib-thalidomide-dexamethasone (VTD/VTD-PACE: n = 52) and 21% melphalan-prednisone-thalidomide (MPT: n = 49). Other drug regimens consisted in melphalan-prednisone (MP: 7%, n = 17), lenalidomide-dexamethasone (RD) (4%, n = 9), bortezomib-cyclophosphamide-dexamethasone (VCD: n = 1) and bortezomib-bendamustine-dexamethasone (VBD: n = 1). Type of drug regimens and allocation by age class (±65 years) were in accordance with current recommendations.

CONCLUSIONS

This study demonstrates the feasibility of identifying complex drug regimens in onco-haematology, using both outpatient and inpatient drug records in French health insurance databases.