A validated algorithm for register-based identification of patients with recurrence of breast cancer—Based on Danish Breast Cancer Group (DBCG) data

Rasmussen, Linda Aagaard; Jensen, Henry; Virgilsen, Line Flytkjær; Thorsen, Lise Bech Jellesmark; Offersen, Birgitte Vrou; Vedsted, Peter

doi:10.1016/j.canep.2019.01.016

Cited by 16 publications

(24 citation statements)

References 22 publications

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“…Furthermore, Aagaard Rasmussen et al´s reference population had a median follow-up of 7.5 years [interquartile range (ICQ) of 5-9 years] since the primary BC surgery and the algorithm was therefore not validated for use in identifying late breast cancer recurrence. 13 Our previous algorithm 14 showed lower sensitivity, specificity and PPV than in the present study. However, we did not use the CBC database to exclude second breast cancers.…”

Section: Comparison With Other Studiescontrasting

confidence: 75%

“…Aagaard Rasmussen et al found a high PPV for procedural codes, but they only included patients with both a procedural code and an ICD code for breast cancer (DC50). 13 Our PPV increased slightly when we added DC50 to the procedural codes. The evidence from our medical record review suggests that surgery many years after a primary breast cancer may represent prophylactic mastectomy, which may explain the observed poorer PPV for procedural codes.…”

Section: Comparison With Other Studiesmentioning

confidence: 84%

“…Two other Danish studies developed and validated algorithms to ascertain breast cancer recurrence using Danish administrative data. 13,14 The latter is from our previous work where we found a positive predictive value (PPV) of 71%. 14 Neither of these algorithms focused on late breast cancer recurrence.…”

Section: Introductionmentioning

confidence: 85%

“…Our PPV was lower than that reported in a previous breast cancer study by Aagaard Rasmussen et al (94%). 13 This may be due to several reasons. Their reference standard did not distinguish recurrent from second primary breast cancer.…”

Section: Comparison With Other Studiesmentioning

confidence: 99%

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<p>Validation of an Algorithm to Ascertain Late Breast Cancer Recurrence Using Danish Medical Registries</p>

Pedersen

Öztürk

Mellemkjær

et al. 2020

CLEP

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We constructed an algorithm to ascertain late breast cancer recurrence-which we define as breast cancer that recurs 10 years or more after primary diagnosis (excluding contralateral breast cancers)-using Danish nationwide medical registries. We used clinical information recorded in medical records as a reference standard. Methods: Using the Danish Breast Cancer Group clinical database, we ascertained data on 21,134 women who survived recurrence-free 10 years or more after incident stage I-III breast cancer diagnosed in 1987-2004. We used a combination of Danish registries to construct the algorithm-the Danish National Patient Registry for information on diagnostic, therapeutic and procedural codes; and cancer diagnoses from the Danish Pathology Registry, the Danish Cancer Registry and the Contralateral Breast Cancer database. To estimate the positive predictive value (PPV), we selected 105 patients who, according to our algorithm, had late recurrence diagnosed at Aarhus University Hospital. To estimate the sensitivity, specificity and negative predictive value (NPV), we selected 114 patients diagnosed with primary breast cancer at Aalborg University Hospital. We abstracted clinical information on late recurrence for patients with medical record-confirmed late recurrence at Aarhus University Hospital. Results: Our algorithm had a PPV of late recurrence of 85.7% (95% CI: 77.5-91.3%), a sensitivity of 100.0% (95% CI, 39.8-100.0%), a specificity of 97.3 (95% CI, 92.2-99.4) and a NPV of 100% (95% CI, 96.6-100.0%). Conclusion: Our algorithm for late recurrence showed a moderate to high PPV and high sensitivity, specificity and negative predictive value. The algorithm could be an important tool for future studies of late breast cancer recurrence.

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Section: Comparison With Other Studiescontrasting

confidence: 75%

Section: Comparison With Other Studiesmentioning

confidence: 84%

Section: Introductionmentioning

confidence: 85%

Section: Comparison With Other Studiesmentioning

confidence: 99%

See 2 more Smart Citations

<p>Validation of an Algorithm to Ascertain Late Breast Cancer Recurrence Using Danish Medical Registries</p>

Pedersen

Öztürk

Mellemkjær

et al. 2020

CLEP

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“…Hence, patients with CR were identified by validated algorithms based on Danish national health registers (Erichsen et al, 2010;Gjerstorff, 2011;Ingeholm, Gögenür, & Iversen, 2016;Schmidt et al, 2015). These algorithms have been described in detail elsewhere (Lash et al, 2015;Rasmussen, Jensen, Virgilsen, Jensen, & Vedsted, 2018;Rasmussen et al, 2019). The algorithms identified patients registered with procedure codes in the Danish National Patient Register (DNPR; Schmidt et al, 2015) corresponding to curative cancer treatment regimens (Figure 1), that is primary cancer surgery and either surgery or radiotherapy corresponding to curative treatment (≥15 fractions) for bladder cancer.…”

Section: Follow-up For Cr and Spcmentioning

confidence: 99%

Time from incident primary cancer until recurrence or second primary cancer: Risk factors and impact in general practice

et al. 2019

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Objective Specialised follow‐up care after cancer treatment is changing towards increased involvement of general practice. To ensure timely detection of new cancer events, knowledge is warranted on the timing of cancer recurrence (CR) and second primary cancer (SPC), including risk factors for CR. Methods This population‐based register study included 67,092 patients diagnosed with malignant melanoma, bladder, lung, ovarian, endometrial, colorectal and breast cancer in Denmark in 2008–2016. The time from primary cancer to CR or SPC and risk factors for prolonged time to CR were analysed and stratified on sex and primary cancer type. Results Cancer recurrence proportions ranged from 6% to 35%. The risk of CR increased profoundly within the first 3 years and then levelled off, except for breast cancer. A total of 3%–6% of patients had SPC, with monotonously increasing cumulative incidence proportions. Besides primary tumour characteristics, lower educational level, living alone and comorbidity were associated with earlier CR. For example, in female malignant melanoma, HRs and 95% confidence intervals were 0.47 (0.37–0.61) for high educational level, 1.40 (1.16–1.68) for living alone and 2.38 (1.53–3.70) for high comorbidity. Conclusion The results may inform stratified risk assessment in decision of frequency, location and duration of post‐cancer follow‐up care.

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Validated algorithms for identifying timing of second event of oropharyngeal squamous cell carcinoma using real‐world data

et al. 2022

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Background: Understanding occurrence and timing of second events (recurrence and second primary cancer) is essential for cancer specific survival analysis. However, this information is not readily available in administrative data. Methods: Alberta Cancer Registry, physician claims, and other administrative data were used. Timing of second event was estimated based on our developed algorithm. For validation, the difference, in days between the algorithm estimated and the chart-reviewed timing of second event. Further, the result of Coxregression modeling cancer-free survival was compared to chart review data.Results: Majority (74.3%) of the patients had a difference between the chartreviewed and algorithm-estimated timing of second event falling within the 0-60 days window. Kaplan-Meier curves generated from the estimated data and chart review data were comparable with a 5-year second-event-free survival rate of 75.4% versus 72.5%. Conclusion:The algorithm provided an estimated timing of second event similar to that of the chart review.

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A validated algorithm for register-based identification of patients with recurrence of breast cancer—Based on Danish Breast Cancer Group (DBCG) data

Cited by 16 publications

References 22 publications

<p>Validation of an Algorithm to Ascertain Late Breast Cancer Recurrence Using Danish Medical Registries</p>

<p>Validation of an Algorithm to Ascertain Late Breast Cancer Recurrence Using Danish Medical Registries</p>

Time from incident primary cancer until recurrence or second primary cancer: Risk factors and impact in general practice

Validated algorithms for identifying timing of second event of oropharyngeal squamous cell carcinoma using real‐world data

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