Do Cancer Genetics Impact Treatment Decision Making? Immunotherapy and Beyond in the Management of Advanced and Metastatic Urothelial Carcinoma.

Bladder cancer is one of the most commonly diagnosed genitourinary malignancies. For many years, the primary treatment for metastatic urothelial cancer (mUC) was predicated on the use of platinum-based chemotherapy. More recently, immune checkpoint inhibitors (ICIs) were approved by regulatory agencies such as the US FDA for use in both the first- and second-line settings. This review outlines the approved ICIs for mUC in the second-line setting and as an alternative to chemotherapy in the first-line setting, as well as the novel agents that have also been incorporated into the treatment of this malignancy. Single-agent ICIs are often used in second-line settings in mUC, and there are three drugs currently approved for those who progress after receiving platinum-based chemotherapy. In the first-line setting, the preferred treatment regimen remains cisplatin-based chemotherapy. However, single-agent ICI can be an alternative first-line treatment for those who are not candidates for cisplatin-based therapy. There are also clinical trials adding ICIs to chemotherapy as combination regimens. However, treatment for mUC has now expanded even beyond immunotherapy. Newer targeted agents such as erdafitinib, a fibroblast growth factor receptor inhibitor, and two antibody-drug conjugates, enfortumab vedotin and sacituzumab govitecan, have been recently approved. As new drug agents are discovered, it will be important to assess both the treatment outcomes as well as the effects on patients' quality of life. Furthermore, integrating genetic and molecular information can help guide treatment decisions as next-generation sequencing is more commonly acquired during the evaluation of newly diagnosed patients with advanced and metastatic cancer.

The Potential Revolution of Cancer Treatment with CRISPR Technology.

Immuno-oncology (IO) and targeted therapies, such as small molecule inhibitors, have changed the landscape of cancer treatment and prognosis; however, durable responses have been difficult to achieve due to tumor heterogeneity, development of drug resistance, and adverse effects that limit dosing and prolonged drug use. To improve upon the current medicinal armamentarium, there is an urgent need for new ways to understand, reverse, and treat carcinogenesis. Clustered regularly interspaced short palindromic repeats (CRISPR)-CRISPR-associated protein (Cas) 9 is a powerful and efficient tool for genome editing that has shown significant promise for developing new therapeutics. While CRISPR/Cas9 has been successfully used for pre-clinical cancer research, its use in the clinical setting is still in an early stage of development. The purpose of this review is to describe the CRISPR technology and to provide an overview of its current applications and future potential as cancer therapies.

Experiences of Women With Interstitial Cystitis/Bladder Pain Syndrome: What Can We Learn From Women's Online Discussions?

PURPOSE: Interstitial cystitis/bladder pain syndrome is a debilitating chronic condition that disproportionately affects women at a ratio of 5:1. We sought to capture women's experiences with interstitial cystitis/bladder pain syndrome by conducting a large-scale digital ethnographic analysis of anonymous posts on Internet forums. MATERIALS AND METHODS: Online posts were identified using condition-specific keywords and data mining extraction services. Once posts were identified, a random sample of 200 online posts was coded and analyzed by hand using qualitative methods. A Latent Dirichlet Allocation probabilistic topic model was applied to the complete dataset to substantiate the qualitative analysis and allow for further thematic discovery. RESULTS: A total of 6,842 posts written by 3,902 unique users from 224 websites were identified. There was a significant overlap between the hand coding and Latent Dirichlet Allocation themes. Our analysis yielded the following themes: online community engagement, triggers and disease etiologies, medical comorbidities, quality of life impact, patient experience with medical care, and alternative therapies and self-management strategies. Additionally, our population appeared to have a high burden of nonurological associated syndromes. We identified barriers to patient-centered care and found that online peer support was important for women. CONCLUSIONS: Our digital ethnographic analysis is a novel application of qualitative methods using online sources. Social media analytics appears to capture a broader patient population than that typically included in clinic-based qualitative studies, such as patient interviews and focus groups. Understanding patient behaviors and concerns are important to guide strategies for improving care and the overall experience with this difficult-to-treat condition.

Using Large-scale Social Media Analytics to Understand Patient Perspectives About Urinary Tract Infections: Thematic Analysis.

BACKGROUND: Current qualitative literature about the experiences of women dealing with urinary tract infections (UTIs) is limited to patients recruited from tertiary centers and medical clinics. However, traditional focus groups and interviews may limit what patients share. Using digital ethnography, we analyzed free-range conversations of an online community. OBJECTIVE: This study aimed to investigate and characterize the patient perspectives of women dealing with UTIs using digital ethnography. METHODS: A data-mining service was used to identify online posts. A thematic analysis was conducted on a subset of the identified posts. Additionally, a latent Dirichlet allocation (LDA) probabilistic topic modeling method was applied to review the entire data set using a semiautomatic approach. Each identified topic was generated as a discrete distribution over the words in the collection, which can be thought of as a word cloud. We also performed a thematic analysis of the word cloud topic model results. RESULTS: A total of 83,589 posts by 53,460 users from 859 websites were identified. Our hand-coding inductive analysis yielded the following 7 themes: quality-of-life impact, knowledge acquisition, support of the online community, health care utilization, risk factors and prevention, antibiotic treatment, and alternative therapies. Using the LDA topic model method, 105 themes were identified and consolidated into 9 categories. Of the LDA-derived themes, 25.7% (27/105) were related to online community support, and 22% (23/105) focused on UTI risk factors and prevention strategies. CONCLUSIONS: Our large-scale social media analysis supports the importance and reproducibility of using online data to comprehend women's UTI experience. This inductive thematic analysis highlights patient behavior, self-empowerment, and online media utilization by women to address their health concerns in a safe, anonymous way.

Social media analytics of overactive bladder posts: what do patients know and want to know?

OBJECTIVE: To assess women's knowledge, patient experience, and treatment decision making regarding overactive bladder (OAB) using digital ethnography. METHODS: Online posts were identified using a data mining service. Two hundred randomized posts were reviewed and coded using grounded theory. We then applied a latent Dirichlet allocation (LDA) probabilistic topic modeling process to review the entire collection of identified posts. RESULTS: A total of 2618 posts by 1867 unique users from 203 different websites were identified. Our analysis yielded six themes: the impact of OAB on quality of life, patient-physician interactions, online engagement, symptom management, patient knowledge acquisition, and alternative therapies. CONCLUSION: Overall, online communities are a source of support for women to self-manage the OAB symptom complex and help overcome treatment pathway challenges. Digital ethnography provides insight into patient knowledge and barriers to patient-centered care, which are important to improve patient outreach. Additionally, we identify similar findings to prior work, indicating the reliability of studying social media.

Female Lower Urinary Tract Symptom Prevention and Treatment Strategies on Social Media: Mixed Correlation With Evidence.

OBJECTIVE: To evaluate the level of evidence behind recommendations on social media for disease prevention in five lower urinary tract symptoms. MATERIALS AND METHODS: We conducted a digital analysis of anonymous online posts on social media sites collected by a social media data mining service. One thousand posts about pelvic organ prolapse, stress urinary incontinence, overactive bladder, urinary tract infection, and interstitial cystitis/bladder pain syndrome were randomly selected. We analyzed these posts for recommendations regarding the prevention and treatment of these diseases, which were then compared to recommendations in available clinical guidelines and assessed for level of evidence. RESULTS: A total of 158 of 1000 posts contained 239 prevention strategies. For pelvic organ prolapse, there were 41 strategies identified, 25 (61%) of which had no evidence. For urinary tract infection 14 of 58 (29%) had no evidence, including recommendations for dietary modifications and urinary alkalization. For overactive bladder 8 of 28 (29%) had level 4 or no evidence. For stress urinary incontinence, 12 of 34 (36%) of prevention strategies had no evidence, such as laser rejuvenation and bladder training. Interstitial cystitis had the highest number of prevention strategies, and most were low or nonevidence based (70/79, 89%). CONCLUSION: Prevention and treatment strategies are common in online discussions of pelvic floor disorders, but at least one third of these recommendations have no evidential support. There is a role for further online education and social media engagement by health care specialists to promote evidence-based practices.

Using Digital Ethnography to Understand the Experience of Women With Pelvic Organ Prolapse.

OBJECTIVE: To characterize the decision-making process and illness experience of women with pelvic organ prolapse (POP) using large-scale social media analysis. METHODS: Digital ethnographic analysis of online posts identified through data mining was performed. Grounded theory methodology was applied to 200 posts via traditional hand coding. To supplement our qualitative approach, we applied a Latent Dirichlet Allocation probabilistic topic modeling process to review the entire data set of identified posts to ensure thematic saturation. RESULTS: There were 3451 posts by 2088 unique users from 117 websites worldwide that were identified via social media data mining. We found that the anonymity of online forums allowed for information and support exchange among women with POP. Our analysis revealed that the exchange of online information aids in the decision-making process and, in some instances, appears to be the primary source of information. There was confusion about the anatomical and surgical complexities of prolapse. Our study also identified misconceptions, perceived risk factors, prevention methods, and management recommendations that were discussed online. CONCLUSIONS: This large-scale online community-based analysis demonstrated the utility of social media to better understand women's experiences with POP. Thematic findings highlighted essential concerns and challenges involved in the surgical decision-making process and the understating of the anatomical complexity of sector defects, specifically to cystocele, rectocele, State specific defects.

Women's Experience with Stress Urinary Incontinence: Insights from Social Media Analytics.

PURPOSE: We conducted a large-scale digital ethnographic analysis of anonymous online posts to capture the complete patient experience, knowledge and perceptions among women with stress urinary incontinence. MATERIALS AND METHODS: Online posts were identified through data mining. Overall, 200 randomized posts were analyzed using grounded theory qualitative methods. To ensure full thematic discovery we also applied a Latent Dirichlet Allocation probabilistic topic modeling approach to the entire data set of identified posts. Latent Dirichlet Allocation topics are represented as a distribution of words, similar to a word cloud, which were manually reviewed to identify themes. RESULTS: A total of 985 online posts by 762 unique users were extracted from 98 websites. There was significant overlap between the grounded theory and Latent Dirichlet Allocation identified themes. Our analysis suggests that these online communities help women manage the quality of life impact of their stress urinary incontinence, navigate specialty care and reach a decision regarding surgical vs nonsurgical management. Additionally, we identified risk factors, prevention strategies and treatment recommendations discussed online. CONCLUSIONS: Findings demonstrated patient values that may influence decision making when seeking care for stress urinary incontinence and choosing a treatment. Social media interactions provide insight into patient behaviors that are important in order to improve patient centered care and decision making.