Health state transitions are reflected in characteristic changes in the molecular composition of biofluids. Detecting these changes in parallel, across a broad spectrum of molecular species, could contribute to the detection of abnormal physiologies. Fingerprinting of biofluids by infrared vibrational spectroscopy offers that capacity. Whether its potential for health monitoring can indeed be exploited critically depends on how stable infrared molecular fingerprints (IMFs) of individuals prove to be over time. Here we report a proof-of-concept study that addresses this question. Using Fourier-transform infrared spectroscopy, we have fingerprinted blood serum and plasma samples from 31 healthy, non-symptomatic individuals, who were sampled up to 13 times over a period of 7 weeks and again after 6 months. The measurements were performed directly on liquid serum and plasma samples, yielding a time- and cost-effective workflow and a high degree of reproducibility. The resulting IMFs were found to be highly stable over clinically relevant time scales. Single measurements yielded a multiplicity of person-specific spectral markers, allowing individual molecular phenotypes to be detected and followed over time. This previously unknown temporal stability of individual biochemical fingerprints forms the basis for future applications of blood-based infrared spectral fingerprinting as a multiomics-based mode of health monitoring.
Recent omics analyses of human biofluids provide opportunities to probe selected species of biomolecules for disease diagnostics. Fourier-transform infrared (FTIR) spectroscopy investigates the full repertoire of molecular species within a sample at once. Here, we present a multi-institutional study in which we analysed infrared fingerprints of plasma and serum samples from 1639 individuals with different solid tumours and carefully matched symptomatic and non-symptomatic reference individuals. Focusing on breast, bladder, prostate, and lung cancer, we find that infrared molecular fingerprinting is capable of detecting cancer: training a support vector machine algorithm allowed us to obtain binary classification performance in the range of 0.78–0.89 (area under the receiver operating characteristic curve [AUC]), with a clear correlation between AUC and tumour load. Intriguingly, we find that the spectral signatures differ between different cancer types. This study lays the foundation for high-throughput onco-IR-phenotyping of four common cancers, providing a cost-effective, complementary analytical tool for disease recognition.
Background: From the clinic’s point of view economic patient care requires comparison and adjustment of costs to revenues. To verify cost coverage for implants in mastectomy with immediate breast reconstruction, a comprehensive cost-reimbursement analysis was performed. Methods: Retrospective analysis of the German diagnosis-related group (G-DRG) revenues for implants from the DRG Browser 2007/2009HA and comparison with actual costs for implants in 2009 from the annual clinic report and the database of the controlling department. Calculation of the relative cost coverage for implants in unilateral (DRG J06Z) and bilateral mastectomy (DRG J16Z). Results: In 2009, n = 98 J06Z and n = 18 J16Z were performed. DRG-calculated expenses for implants were € 69.65 for J06Z and € 123.07 for J16Z, i.e. a total of € 9,040.96. Actual costs for all implants were € 121,645.60, mean € 699.11 (€ 404.94–1,171.44). Attributable implant costs for 100% immediate breast reconstruction rate were € 93,679.28. Thus, implants are not cost covering by –90.3% (–82.8 to –94.7%). Subsidies for implants from the clinic’s budget range from € 335.29 to € 2,219.81 per case. Conclusions: Immediate breast reconstruction with implants after mastectomy is – even 6 years after introduction of the DRGs – not adequately calculated to be cost covering since the actual implant costs exceed the calculated revenues by far. At present, these implants are subsidized by the clinic at, on average, 90.3%. If economic patient care is mandatory, a maximum of only 1 in 10 patients with mastectomy can be offered immediate breast reconstruction with implants in Germany.
<b><i>Introduction:</i></b> Breast cancer (BC) is the most common cancer in women worldwide. Despite screening and information efforts, about 10% of patients present with tumor size T3 or T4 at primary diagnosis. Late presentation is associated with more advanced tumor stage and consecutively with worse survival rates. <b><i>Objective:</i></b> This study aimed to evaluate whether patients with a late presentation at primary BC diagnosis differ in their personality from those with early diagnosis. <b><i>Methods:</i></b> In this bicentric, observational study, personality traits, positive and negative affectivity, anxiety, spirituality, illness beliefs, and sociodemographic characteristics were assessed in BC patients who presented with T-stages 3 or 4 (late presenters) and T-stages 1 or 2 (controls) at initial diagnosis. <b><i>Results:</i></b> Forty patients (20 controls, 20 late presenters) were interviewed. “Late presenters” perceived their disease as long lasting and had significantly more “positive affectivity” in the current trait. Although no significant associations were found, there was a trend for late presenters to have higher education levels, less spiritual longing, less accurate explanation of their illness, less anxiety in the trait scale, and more conscientiousness than the controls. <b><i>Conclusion:</i></b> As patients with late presentation for BC differ in specific psychological and sociodemographic characteristics from patients with early BC, the findings of this pilot project warrant additional investigations to identify further specific characteristics and motivations. Identifying patients at risk for late presentation and encouraging them to accept an earlier diagnosis could help to improve their therapy and, finally, their outcome.
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