Matthew R. Jensen

Increased long-term survival of posterior cruciate-retaining versus posterior cruciate-stabilizing total knee replacements.

BACKGROUND Considerable debate remains regarding the use of posterior cruciate-retaining or posterior cruciate-stabilizing designs for total knee arthroplasty. Multiple studies have investigated kinematic, radiographic, and clinical outcomes of both. Nevertheless, long-term survivorship analyses directly comparing the two designs have not been performed, to our knowledge. Our goal was to analyze the fifteen-year survival of posterior cruciate-retaining and posterior cruciate-stabilizing total knee replacements at our institution. METHODS A retrospective review identified 8117 total knee arthroplasties (5389 posterior cruciate-retaining and 2728 posterior cruciate-stabilizing) that had been performed from 1988 to 1998. This range was chosen because both designs were used in high volumes at our institution during this period. Patients were followed via our total joint registry at one, two, and five years after the arthroplasty and every five years thereafter. Aseptic revision surgery was the primary end point of our analysis. Implant survival was estimated with Kaplan-Meier curves. RESULTS Survival at fifteen years was 90% for posterior cruciate-retaining total knee replacements, compared with 77% for posterior cruciate-stabilizing total knee replacements (p < 0.001). In knees with preoperative deformity, the fifteen-year survival was 90% for posterior cruciate-retaining total knee replacements, compared with 75% for posterior cruciate-stabilizing total knee replacements (p < 0.04). Likewise, in knees without preoperative deformity, the fifteen-year survival was 88% for posterior cruciate-retaining total knee replacements, compared with 78% for posterior cruciate-stabilizing total knee replacements (p < 0.001). After adjustment for age, sex, preoperative diagnosis, and preoperative deformity, the risk of revision was significantly lower in knees with a posterior cruciate-retaining total knee replacement (p < 0.001; hazard ratio = 0.5; 95% confidence interval, 0.4 to 0.6). CONCLUSIONS In evaluating the implants used at our institution for total knee arthroplasty during the study period, posterior cruciate-retaining prostheses had significantly improved survival in comparison with posterior cruciate-stabilizing prostheses at fifteen years. Furthermore, this significant difference remained when accounting for age, sex, diagnosis, and deformity.

Cardiac and thromboembolic complications and mortality in patients undergoing total hip and total knee arthroplasty

Objective To study 90-day complications following total hip arthroplasty (THA) or total knee arthroplasty (TKA). Method In a population-based cohort of all Olmsted County residents who underwent a THA or TKA (1994-2008), we assessed 90-day occurrence and predictors of cardiac complications (myocardial infarction, cardiac arrhythmia or congestive heart failure), thromboembolic complications (deep venous thrombosis or pulmonary embolism) and mortality. Results 90-day complication rates after THA and TKA were: cardiac, 6.9% and 6.7%; thromboembolic, 4.0% and 4.9%; and mortality, 0.7% and 0.4%, respectively. In multivariable-adjusted logistic regression analyses, ASA class III–IV (OR 6.1, 95% CI:1.6-22.8) and higher Deyo–Charlson comorbidity score (OR 1.2, 95% CI:1.0-1.4) were significantly associated with odds of 90-day cardiac event post-THA in patients with no known previous cardiac event. In those with known previous cardiac disease, ASA class III–IV (OR 4.4, 95% CI:2.0-9.9), male gender (OR 0.5, 95% CI:0.3-0.9) and history of thromboembolic disease (OR 3.2; 95% CI:1.4-7.0) were significantly associated with odds of cardiac complication 90 days post-THA. No significant predictors of thromboembolism were found in THA patients. In TKA patients with no previous cardiac history, age >65 years (OR 4.1, 95% CI:1.2-14.0) and in TKA patients with known cardiac disease, ASA class III–IV (OR 3.2, 95% CI:1.8-5.7) was significantly associated with odds of 90-day cardiac events. In TKA patients with no previous thromboembolic disease, male gender (OR 0.5, 95% CI:0.2-0.9) and higher Charlson index (OR 1.2, 95% CI:1.1-1.3) and in patients with known thromboembolic disease, higher Charlson index score (OR 1.2, 95% CI:1.1-1.4) was associated with odds of 90-day thromboembolic events. Conclusion Older age, higher comorbidity, higher ASA class and previous history of cardiac/thromboembolic disease were associated with an increased risk.

The Contributions of Breast Density and Common Genetic Variation to Breast Cancer Risk

We evaluated whether a 76-locus polygenic risk score (PRS) and Breast Imaging Reporting and Data System (BI-RADS) breast density were independent risk factors within three studies (1643 case patients, 2397 control patients) using logistic regression models. We incorporated the PRS odds ratio (OR) into the Breast Cancer Surveillance Consortium (BCSC) risk-prediction model while accounting for its attributable risk and compared five-year absolute risk predictions between models using area under the curve (AUC) statistics. All statistical tests were two-sided. BI-RADS density and PRS were independent risk factors across all three studies (P interaction = .23). Relative to those with scattered fibroglandular densities and average PRS (2(nd) quartile), women with extreme density and highest quartile PRS had 2.7-fold (95% confidence interval [CI] = 1.74 to 4.12) increased risk, while those with low density and PRS had reduced risk (OR = 0.30, 95% CI = 0.18 to 0.51). PRS added independent information (P < .001) to the BCSC model and improved discriminatory accuracy from AUC = 0.66 to AUC = 0.69. Although the BCSC-PRS model was well calibrated in case-control data, independent cohort data are needed to test calibration in the general population.

Comparison of Clinical and Automated Breast Density Measurements: Implications for Risk Prediction and Supplemental Screening

Purpose To compare the classification of breast density with two automated methods, Volpara (version 1.5.0; Matakina Technology, Wellington, New Zealand) and Quantra (version 2.0; Hologic, Bedford, Mass), with clinical Breast Imaging Reporting and Data System (BI-RADS) density classifications and to examine associations of these measures with breast cancer risk. Materials and Methods In this study, 1911 patients with breast cancer and 4170 control subjects matched for age, race, examination date, and mammography machine were evaluated. Participants underwent mammography at Mayo Clinic or one of four sites within the San Francisco Mammography Registry between 2006 and 2012 and provided informed consent or a waiver for research, in compliance with HIPAA regulations and institutional review board approval. Digital mammograms were retrieved a mean of 2.1 years (range, 6 months to 6 years) before cancer diagnosis, with the corresponding clinical BI-RADS density classifications, and Volpara and Quantra density estimates were generated. Agreement was assessed with weighted κ statistics among control subjects. Breast cancer associations were evaluated with conditional logistic regression, adjusted for age and body mass index. Odds ratios, C statistics, and 95% confidence intervals (CIs) were estimated. Results Agreement between clinical BI-RADS density classifications and Volpara and Quantra BI-RADS estimates was moderate, with κ values of 0.57 (95% CI: 0.55, 0.59) and 0.46 (95% CI: 0.44, 0.47), respectively. Differences of up to 14% in dense tissue classification were found, with Volpara classifying 51% of women as having dense breasts, Quantra classifying 37%, and clinical BI-RADS assessment used to classify 43%. Clinical and automated measures showed similar breast cancer associations; odds ratios for extremely dense breasts versus scattered fibroglandular densities were 1.8 (95% CI: 1.5, 2.2), 1.9 (95% CI: 1.5, 2.5), and 2.3 (95% CI: 1.9, 2.8) for Volpara, Quantra, and BI-RADS classifications, respectively. Clinical BI-RADS assessment showed better discrimination of case status (C = 0.60; 95% CI: 0.58, 0.61) than did Volpara (C = 0.58; 95% CI: 0.56, 0.59) and Quantra (C = 0.56; 95% CI: 0.54, 0.58) BI-RADS classifications. Conclusion Automated and clinical assessments of breast density are similarly associated with breast cancer risk but differ up to 14% in the classification of women with dense breasts. This could have substantial effects on clinical practice patterns. (©) RSNA, 2015 Online supplemental material is available for this article.

Are Gender, Comorbidity, and Obesity Risk Factors for Postoperative Periprosthetic Fractures After Primary Total Hip Arthroplasty?

We studied the frequency and patient risk factors for postoperative periprosthetic fractures after primary total hip arthroplasty (THA). With a mean follow-up of 6.3 years, 305 postoperative periprosthetic fractures occurred in 14,065 primary THAs. In multivariable-adjusted Cox regression analyses, female gender (hazard ratio [HR], 1.48; 95% confidence interval [CI], 1.17-1.88), Deyo-Charlson comorbidity score of 2 (HR, 1.74 for score of 2; 95% CI, 1.25-2.43) or 3 or higher (HR, 1.71; 95% CI, 1.26-2.32), and American Society of Anesthesiologist class of 2 (HR, 1.84; 95% CI, 0.90-3.76) or 3 (HR, 2.45; 95% CI, 1.18-5.1) or 4 or higher (HR, 2.68; 95% CI, 0.70-10.28) were significantly associated with higher risk/hazard, and cemented implant, with lower hazard (HR, 0.68; 95% CI, 0.54-0.87) of postoperative periprosthetic fractures. Interventions targeted at optimizing comorbidity management may decrease postoperative fractures after THA.

The influence of mammogram acquisition on the mammographic density and breast cancer association in the mayo mammography health study cohort

IntroductionMammographic density is a strong risk factor for breast cancer. Image acquisition technique varies across mammograms to limit radiation and produce a clinically useful image. We examined whether acquisition technique parameters at the time of mammography were associated with mammographic density and whether the acquisition parameters confounded the density and breast cancer association.MethodsWe examined this question within the Mayo Mammography Health Study (MMHS) cohort, comprised of 19,924 women (51.2% of eligible) seen in the Mayo Clinic mammography screening practice from 2003 to 2006. A case-cohort design, comprising 318 incident breast cancers diagnosed through December 2009 and a random subcohort of 2,259, was used to examine potential confounding of mammogram acquisition technique parameters (x-ray tube voltage peak (kVp), milliampere-seconds (mAs), thickness and compression force) on the density and breast cancer association. The Breast Imaging Reporting and Data System four-category tissue composition measure (BI-RADS) and percent density (PD) (Cumulus program) were estimated from screen-film mammograms at time of enrollment. Spearman correlation coefficients (r) and means (standard deviations) were used to examine the relationship of density measures with acquisition parameters. Hazard ratios (HR) and C-statistics were estimated using Cox proportional hazards regression, adjusting for age, menopausal status, body mass index and postmenopausal hormones. A change in the HR of at least 15% indicated confounding.ResultsAdjusted PD and BI-RADS density were associated with breast cancer (p-trends < 0.001), with a 3 to 4-fold increased risk in the extremely dense vs. fatty BI-RADS categories (HR: 3.0, 95% CI, 1.7 - 5.1) and the ≥ 25% vs. ≤ 5% PD categories (HR: 3.8, 95% CI, 2.5 - 5.9). Of the acquisition parameters, kVp was not correlated with PD (r = 0.04, p = 0.07). Although thickness (r = -0.27, p < 0.001), compression force (r = -0.16, p < 0.001), and mAs (r = -0.06, p = 0.008) were inversely correlated with PD, they did not confound the PD or BI-RADS associations with breast cancer and their inclusion did not improve discriminatory accuracy. Results were similar for associations of dense and non-dense area with breast cancer.ConclusionsWe confirmed a strong association between mammographic density and breast cancer risk that was not confounded by mammogram acquisition technique.

Dense and Nondense Mammographic Area and Risk of Breast Cancer by Age and Tumor Characteristics

Background: Mammographic density (MD) is a strong breast cancer risk factor. We previously reported associations of percent mammographic density (PMD) with larger and node-positive tumors across all ages, and estrogen receptor (ER)–negative status among women ages <55 years. To provide insight into these associations, we examined the components of PMD [dense area (DA) and nondense area (NDA)] with breast cancer subtypes. Methods: Data were pooled from six studies including 4,095 breast cancers and 8,558 controls. DA and NDA were assessed from digitized film-screen mammograms and standardized across studies. Breast cancer odds by density phenotypes and age according to histopathologic characteristics and receptor status were calculated using polytomous logistic regression. Results: DA was associated with increased breast cancer risk [OR for quartiles: 0.65, 1.00 (Ref), 1.22, 1.55; Ptrend <0.001] and NDA was associated with decreased risk [ORs for quartiles: 1.39, 1.00 (Ref), 0.88, 0.72; Ptrend <0.001] across all ages and invasive tumor characteristics. There were significant trends in the magnitude of associations of both DA and NDA with breast cancer by increasing tumor size (Ptrend < 0.001) but no differences by nodal status. Among women <55 years, DA was more strongly associated with increased risk of ER+ versus ER− tumors (Phet = 0.02), while NDA was more strongly associated with decreased risk of ER− versus ER+ tumors (Phet = 0.03). Conclusions: DA and NDA have differential associations with ER+ versus ER− tumors that vary by age. Impact: DA and NDA are important to consider when developing age- and subtype-specific risk models. Cancer Epidemiol Biomarkers Prev; 24(5); 798–809. ©2015 AACR.

Predictors of periprosthetic fracture after total knee replacement: an analysis of 21,723 cases.

Background and purpose Periprosthetic fracture is a devastating complication of total knee replacement (TKR). Most published studies have not comprehensively assessed clinical and demographic predictors. We wanted to determine the incidence and predictors of postoperative periprosthetic fracture after primary and revision TKR. Patients and methods We used prospectively collected data in the Mayo Clinic Total Joint Registry on all patients who underwent primary or revision TKR at the Mayo Clinic, Rochester, from 1989 through 2008. We assessed incidence of postoperative periprosthetic fractures and modifiable (comorbidity, body mass index) and unmodifiable factors (age, sex, operative diagnosis, ASA class, previous cardiac disease, and previous thromboembolic disease) as predictors of postoperative periprosthetic fractures. We used multivariable-adjusted Cox regression analyses separately for primary and revision TKR. Results 12,914 patients underwent 17,633 primary TKRs and 3,286 patients underwent 4,090 revision TKRs during the period 1989–2008. 1.1% of patients (188/17,633) after primary TKR and 2.5% of patients (104/4,090) after revision TKR sustained a postoperative periprosthetic fracture on or after postoperative day 1. Older age was associated with lower risk of periprosthetic fractures after primary TKR (p < 0.001). Compared to ≤ 60 years, risk was lower for ages 61–70 years (hazard ratio (HR) = 0.5, 95% confidence interval (CI): 0.3–0.7)) and 71–80 years (HR = 0.6, CI: 0.4–0.8), but not for age > 80 years (HR = 0.9, CI: 0.5–1.6). In revision TKR cohort, a diagnosis of non-union (HR = 4.9, CI: 1.2–20), infection (HR = 2.9, CI: 1.3–6.4) or previous surgery with components removed (HR = 2.1, CI: 1.3–3.4) increased the risk of postoperative periprosthetic fracture, compared to a diagnosis of loosening/wear/osteolysis. Interpretation We identified significant risk factors for periprosthetic fracture after primary and revision TKR. Patients with these risk factors can be informed by their surgeons of increased risk of this uncommon, but serious complication of TKR.

Patient factors predict periprosthetic fractures after revision total hip arthroplasty.

We assessed important patient risk factors for postoperative periprosthetic fractures after revision total hip arthroplasty (THA) using prospectively collected Institutional Joint Registry data. We used univariate and multivariable-adjusted Cox regression analyses. There were 330 postoperative periprosthetic fractures after 6281 revision THAs. In multivariable-adjusted analyses, hazard ratio (95% confidence interval) of periprosthetic fracture was higher for women (1.66 [1.32-2.080], P < .001), a higher Deyo-Charlson comorbidity index of 2 (1.46 [1.03-2.07]) and index of 3+ (2.01 [1.48-2.73]; overall, P < .001), and operative diagnosis, especially previous nonunion (5.76 [2.55-13.02]; overall, P < .001). Hazard ratio was lower in patients 61 to 70 years old (0.64 [0.49-0.84]) and 71 to 80 years old (0.57 [0.43-0.76]) compared with those younger than 60 years (overall, P < .0001). Our study identified important modifiable and unmodifiable risk factors for fractures after revision THA.

Bronchial resection margin length and clinical outcome in non-small cell lung cancer

OBJECTIVE Complete surgical resection with pathologic negative margin is associated with the best prognosis in early-stage non-small-cell lung cancer (NSCLC). However, the impact of the length of the bronchial margin remains unknown. This study aimed to determine whether an increased bronchial resection margin length is correlated with an improved disease-free and overall survival rate. METHODS A total of 3936 consecutive pulmonary resections were performed between 25 June 1992 and 31 December 2007 at Mayo Clinic Rochester. A subset consisting of 496 patients with completely resected lesions (R0-resection), and a documented bronchial margin length was analyzed retrospectively. RESULTS There were 340 men (68.5%) and 156 women (31.5%), with a mean age of 65.9±10.6 years. All patients underwent anatomic lobectomy or larger resection. Final pathology confirmed complete resection without microscopic residual tumor (R0-resection) in all patients. Mean length of the bronchial resection margin was 23.3±15.9mm. Overall, 190 patients (38.3%) suffered from disease recurrence with local recurrence in 35 patients, distant recurrence in 101, and both local and distant recurrence in 54 patients. Overall 5-year and 10-year local recurrence-free survival was 72.5% (95% confidence interval (CI): 67.3-78.1) and 68.0% (95% CI: 62.1-74.4), distant recurrence free survival 61.0% (95% CI: 55.8-66.6) and 52.9% (95% CI: 46.7-60.1) and overall survival 50.0% (95% CI: 45.1-55.3) and 28.8% (95% CI: 23.8-34.7). Tumor size and N-stage were associated with a worse prognosis in terms of local and distant recurrence, as well as survival (p<0.05). Histology was not significantly associated with local recurrence (p=0.28), though adenocarcinoma relative to squamous cell carcinoma was associated with an increased risk of distant recurrence (p<0.01). There was no significant association between type of surgical resection and local (p=0.37) or distant recurrence (p=0.37). Neither local (p=0.56) or distant recurrence (p=0.46), nor survival (p=0.54) was associated with the bronchial margin length. In multivariate models including age, N-stage, and gender there were no significant overall associations of margin length (≤5, 6-10, 11-15, 16-20, >20mm) and local recurrence (p=0.51), distant recurrence (p=0.33), or survival (p=0.75). CONCLUSIONS When complete surgical resection is achieved, the extent of the bronchial margin has no clinically relevant impact on disease-free and overall survival in NSCLC.