Prevalence and Spectrum of Second Primary Malignancies among People Living with HIV in the French Dat’AIDS Cohort

Background: We aimed to describe the prevalence and spectrum of second primary cancer (SPC) in HIV-positive cancer survivors. Methods: A multicenter retrospective study was performed using longitudinal data from the French Dat’AIDS cohort. Subjects who had developed at least two primary cancers were selected. The spectrum of SPCs was stratified by the first primary cancer type and by sex. Results: Among the 44,642 patients in the Dat’AIDS cohort, 4855 were diagnosed with cancer between 1 December 1983 and 31 December 2015, of whom 444 (9.1%) developed at least two primary cancers. The most common SPCs in men were non-Hodgkin lymphoma (NHL) (22.8%), skin carcinoma (10%) and Kaposi sarcoma (KS) (8.4%), and in women the most common SPCs were breast cancer (16%), skin carcinoma (9.3%) and NHL (8%). The pattern of SPCs differed according to first primary cancer and by sex: in men, NHL was the most common SPC after primary KS and KS was the most common SPC after primary NHL; while in women, breast cancer was the most common SPC after primary NHL and primary breast cancer. Conclusion: The frequency and pattern of subsequent cancers among HIV-positive cancer survivors differed according to the first primary cancer type and sex.

Risk of second primary malignancies associated with radiotherapy in prostate cancer patients: competing risk analysis

Background: The effect of radiotherapy (RT) for second primary malignancies (SPMs) among prostate cancer survivors is controversial. Methods: Applying logistic regression, competing risk analysis and propensity score matching method, this study analyzed clinical data from the Surveillance, Epidemiology, and End Results program to compare the risk for SPMs between patients receiving RT and non-RT. Results: In this study, prostate cancer patients treated with RT developed more SPMs in the anus, bladder, rectum, liver, lung and bronchus and lymphoma than non-RT groups. Conclusion: More intensive surveillance should be adopted for these cancers among prostate cancer survivors.

Positron Emission Tomography–Driven Strategy in Advanced Hodgkin Lymphoma: Prolonged Follow-Up of the AHL2011 Phase III Lymphoma Study Association Study

PURPOSE The AHL2011 study (ClinicalTrials.gov identifier: NCT01358747 ) demonstrated that a positron emission tomography (PET)-driven de-escalation strategy after two cycles of bleomycin, etoposide, doxorubicin, cyclophosphamide, vincristine, procarbazine, and prednisone (BEACOPP) provides similar progression-free survival (PFS) and overall survival (OS) and reduces early toxicity compared with a nonmonitored standard treatment. Here, we report, with a prolonged follow-up, the final study results. METHODS Patients with advanced Hodgkin lymphoma (stage III, IV, or IIB with mediastinum/thorax ratio > 0.33 or extranodal involvement) age 16-60 years were prospectively randomly assigned between 6 × BEACOPP and a PET-driven arm after 2 × BEACOPP delivering 4 × ABVD (doxorubicin, bleomycin, vinblastine, and dacarbazine) in PET2– and 4 × BEACOPP in PET2+ patients. PET performed after four cycles of chemotherapy had to be negative to complete the planned treatment. RESULTS In total, 823 patients were enrolled including 413 in the standard arm and 410 in the PET-driven arm. With a 67.2-month median follow-up, 5-year PFS (87.5% v 86.7%; hazard ratio [HR] = 1.07; 95% CI, 0.74 to 1.57; P = .67) and OS (97.7% in both arms; HR = 1.012; 95% CI, 0.50 to 2.10; P = .53) were similar in both randomization arms. In the whole cohort, full interim PET assessment predicted patients' 5-year PFS (92.3% in PET2–/PET4–, 75.4% [HR = 3.26; 95% CI, 18.3 to 5.77] in PET2+/PET4– and 46.5% [HR = 12.4; 95% CI, 7.31 to 19.51] in PET4+ patients, respectively; P < .0001) independent of international prognosis score. Five-year OS was also affected by interim PET results, and PET2+/PET4– patients (93.5%; HR = 3.3; 95% CI, 1.07 to 10.1; P = .036) and PET4+ patients (91.9%; HR = 3.756; 95% CI, 1.07 to 13.18; P = .038) had a significant lower OS than PET2–/PET4– patients (98.2%). Twenty-two patients (2.7%) developed a second primary malignancy, 13 (3.2%) and 9 (2.2%) in the standard and experimental arms, respectively. CONCLUSION The extended follow-up confirms the continued efficacy and favorable safety of AHL2011 PET-driven strategy, which is noninferior to standard six cycles of BEACOPP. PET4 provides additional prognostic information to PET2 and allows identifying patients with particularly poor prognosis.

Radiomics Study for Discriminating Second Primary Lung Cancers From Pulmonary Metastases in Pulmonary Solid Lesions

BackgroundThe objective of this study was to assess the value of quantitative radiomics features in discriminating second primary lung cancers (SPLCs) from pulmonary metastases (PMs).MethodsThis retrospective study enrolled 252 malignant pulmonary nodules with histopathologically confirmed SPLCs or PMs and randomly assigned them to a training or validation cohort. Clinical data were collected from the electronic medical records system. The imaging and radiomics features of each nodule were extracted from CT images.ResultsA rad-score was generated from the training cohort using the least absolute shrinkage and selection operator regression. A clinical and radiographic model was constructed using the clinical and imaging features selected by univariate and multivariate regression. A nomogram composed of clinical-radiographic factors and a rad-score were developed to validate the discriminative ability. The rad-scores differed significantly between the SPLC and PM groups. Sixteen radiomics features and four clinical-radiographic features were selected to build the final model to differentiate between SPLCs and PMs. The comprehensive clinical radiographic–radiomics model demonstrated good discriminative capacity with an area under the curve of the receiver operating characteristic curve of 0.9421 and 0.9041 in the respective training and validation cohorts. The decision curve analysis demonstrated that the comprehensive model showed a higher clinical value than the model without the rad-score.ConclusionThe proposed model based on clinical data, imaging features, and radiomics features could accurately discriminate SPLCs from PMs. The model thus has the potential to support clinicians in improving decision-making in a noninvasive manner.

Optimization based Tuberculosis Image Segmentation by Ant Colony Heuristic Method

Tuberculosis (TB) is a worldwide health crisis and is the second primary infectious disease that causes death next to human immunodeficiency virus. In this work, an attempt has been made to detect the presence of bacilli in sputum smears. The smear images recorded under standard image acquisition protocol are subjected to hybrid Ant Colony Optimization (ACO)-morphological based segmentation procedure. This method is able to retain the shape of bacilli in TB images. The segmented images are validated with ground truth using overlap, distance and probability-based measures. Significant shape-based features such as area, perimeter, compactness, shape factor and tortuosity are extracted from the segmented images. It is observed that this method preserves more edges, detects the presence of bacilli and facilitates direct segmentation with reduced number of redundant searches to generate edges. Thus this hybrid segmentation technique aid in the diagnostic relevance of TB images in identifying the objects present in them.

Optimization based Tuberculosis Image Segmentation by Ant Colony Heuristic Method

Tuberculosis (TB) is a worldwide health crisis and is the second primary infectious disease that causes death next to human immunodeficiency virus. In this work, an attempt has been made to detect the presence of bacilli in sputum smears. The smear images recorded under standard image acquisition protocol are subjected to hybrid Ant Colony Optimization (ACO)-morphological based segmentation procedure. This method is able to retain the shape of bacilli in TB images. The segmented images are validated with ground truth using overlap, distance and probability-based measures. Significant shape-based features such as area, perimeter, compactness, shape factor and tortuosity are extracted from the segmented images. It is observed that this method preserves more edges, detects the presence of bacilli and facilitates direct segmentation with reduced number of redundant searches to generate edges. Thus this hybrid segmentation technique aid in the diagnostic relevance of TB images in identifying the objects present in them.