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Immunotherapy has made recent improvements in disease-free survival (DFS) and/or overall survival (OS) in all stages of non-small-cell lung cancer (NSCLC). Here, we review the tumor microenvironment and its immunosuppressive effects and discuss how anti-angiogenic therapies may potentiate the anti-carcinogenic effects of immunotherapy. We also review all the past literature and discuss strategies of combining anti-angiogenic therapy and immunotherapy +/- chemotherapy and hypothesize how we can use this strategy for non-small-cell lung cancer in metastatic previously untreated/previously treated settings in previously treated EGFR-mutated NSCLC for the upfront treatment of brain metastases prior to radiation therapy and for the incorporation of this strategy into stage III unresectable disease. We assert the use of anti-angiogenic therapy and immunotherapy when combined appropriately with chemotherapy and radiotherapy has the potential to increase the long-term survivals in both the stage III and metastatic setting so that we can now consider more patients to experience curative treatment.

Objective: The diagnostic criteria of lymphatic vascular invasion have not been standardized. Our investigation assesses the factors associated with lymphatic vascular invasion positive tumors and the impact of lymphatic vascular invasion on overall survival for patients with non-small cell lung cancer undergoing (bi)lobectomy with an adequate node dissection., Methods: The National Cancer Database was queried from the years 2010 to 2015 to find surgical patients who underwent lobectomy with at least 10 lymph nodes examined (adequate node dissection) and with known lymphatic vascular invasion status. Paired t tests were used to distinguish differences between the patients with and without lymphatic vascular invasion in their specimen. Multivariable analysis was used to determine factors associated with overall survival. Propensity score matching adjusting for overall survival factors was used to determine the lymphatic vascular invasion's overall survival impact by grade, histology, p-T/N/overall stage, and tumor size., Results: Lymphatic vascular invasion status was reported in 91.6% and positive in 23.4% of 28,842 eligible patients. Academic medical centers, institutions with populations more than 1,000,000, and the mid-Atlantic region reported higher rates of lymphatic vascular invasion positive tumors as well as overall survival compared with other cancer centers. Lymphatic vascular invasion was independently associated with a significant decrement in overall survival as per multivariable analysis and propensity score matching. Propensity score matching demonstrated that lymphatic vascular invasion was associated with a significant decrement in overall survival for all histologies, tumor grades, tumor sizes, and stages, except for more advanced pathologic stages T3/III/N2 and larger tumors greater than 4 cm for which overall survival was trending worse with lymphatic vascular invasion positive., Conclusions: Lymphatic vascular invasion positive varies based on hospital location/type and population, but it was associated with a decrement in overall survival that was independent of pathologic T/N/overall stage, histology, and tumor grade. Lymphatic vascular invasion must be standardized and considered as a staging variable and should be considered as a sole determinant for prognosis, especially for those with earlier-stage and smaller tumors., Competing Interests: The authors reported no conflicts of interest. The Journal policy requires editors and reviewers to disclose conflicts of interest and to decline handling or reviewing manuscripts for which they may have a conflict of interest. The editors and reviewers of this article have no conflicts of interest., (© 2024 The Author(s).)

Purpose: AI algorithms have shown impressive performance in segmenting geographic atrophy (GA) from fundus autofluorescence (FAF) images. However, selection of artificial intelligence (AI) architecture is an important variable in model development. Here, we explore 12 distinct AI architecture combinations to determine the most effective approach for GA segmentation., Methods: We investigated various AI architectures, each with distinct combinations of encoders and decoders. The architectures included three decoders-FPN (Feature Pyramid Network), UNet, and PSPNet (Pyramid Scene Parsing Network)-and serve as the foundation framework for segmentation task. Encoders including EfficientNet, ResNet (Residual Networks), VGG (Visual Geometry Group) and Mix Vision Transformer (mViT) have a role in extracting optimum latent features for accurate GA segmentation. Performance was measured through comparison of GA areas between human and AI predictions and Dice Coefficient (DC)., Results: The training dataset included 601 FAF images from AREDS2 study and validation included 156 FAF images from the GlaxoSmithKline study. The mean absolute difference between grader measured and AI predicted areas ranged from -0.08 (95% CI = -1.35, 1.19) to 0.73 mm2 (95% CI = -5.75,4.29) and DC between 0.884-0.993. The best-performing models were UNet and FPN frameworks with mViT, and the least-performing models were PSPNet framework., Conclusions: The choice of AI architecture impacts GA segmentation performance. Vision transformers with FPN and UNet architectures demonstrate stronger suitability for this task compared to Convolutional Neural Network- and PSPNet-based models. Selecting an AI architecture must be tailored to the specific goals of the project, and developers should consider which architecture is ideal for their project.

Purpose: To gain an understanding of data labeling requirements to train deep learning models for measurement of geographic atrophy (GA) with fundus autofluorescence (FAF) images., Design: Evaluation of artificial intelligence (AI) algorithms., Subjects: The Age-Related Eye Disease Study 2 (AREDS2) images were used for training and cross-validation, and GA clinical trial images were used for testing., Methods: Training data consisted of 2 sets of FAF images; 1 with area measurements only and no indication of GA location (Weakly labeled) and the second with GA segmentation masks (Strongly labeled)., Main Outcome Measures: Bland-Altman plots and scatter plots were used to compare GA area measurement between ground truth and AI measurements. The Dice coefficient was used to compare accuracy of segmentation of the Strong model., Results: In the cross-validation AREDS2 data set (n = 601), the mean (standard deviation [SD]) area of GA measured by human grader, Weakly labeled AI model, and Strongly labeled AI model was 6.65 (6.3) mm 2 , 6.83 (6.29) mm 2 , and 6.58 (6.24) mm 2 , respectively. The mean difference between ground truth and AI was 0.18 mm 2 (95% confidence interval, [CI], -7.57 to 7.92) for the Weakly labeled model and -0.07 mm 2 (95% CI, -1.61 to 1.47) for the Strongly labeled model. With GlaxoSmithKline testing data (n = 156), the mean (SD) GA area was 9.79 (5.6) mm 2 , 8.82 (4.61) mm 2 , and 9.55 (5.66) mm 2 for human grader, Strongly labeled AI model, and Weakly labeled AI model, respectively. The mean difference between ground truth and AI for the 2 models was -0.97 mm 2 (95% CI, -4.36 to 2.41) and -0.24 mm 2 (95% CI, -4.98 to 4.49), respectively. The Dice coefficient was 0.99 for intergrader agreement, 0.89 for the cross-validation data, and 0.92 for the testing data., Conclusions: Deep learning models can achieve reasonable accuracy even with Weakly labeled data. Training methods that integrate large volumes of Weakly labeled images with small number of Strongly labeled images offer a promising solution to overcome the burden of cost and time for data labeling., Financial Disclosures: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article., (© 2024 by the American Academy of Ophthalmology.)

Purpose: The curation of images using human resources is time intensive but an essential step for developing artificial intelligence (AI) algorithms. Our goal was to develop and implement an AI algorithm for image curation in a high-volume setting. We also explored AI tools that will assist in deploying a tiered approach, in which the AI model labels images and flags potential mislabels for human review., Design: Implementation of an AI algorithm., Participants: Seven-field stereoscopic images from multiple clinical trials., Methods: The 7-field stereoscopic image protocol includes 7 pairs of images from various parts of the central retina along with images of the anterior part of the eye. All images were labeled for field number by reading center graders. The model output included classification of the retinal images into 8 field numbers. Probability scores (0-1) were generated to identify misclassified images, with 1 indicating a high probability of a correct label., Main Outcome Measures: Agreement of AI prediction with grader classification of field number and the use of probability scores to identify mislabeled images., Results: The AI model was trained and validated on 17 529 images and tested on 3004 images. The pooled agreement of field numbers between grader classification and the AI model was 88.3% (kappa, 0.87). The pooled mean probability score was 0.97 (standard deviation [SD], 0.08) for images for which the graders agreed with the AI-generated labels and 0.77 (SD, 0.19) for images for which the graders disagreed with the AI-generated labels ( P  < 0.0001). Using receiver operating characteristic curves, a probability score of 0.99 was identified as a cutoff for distinguishing mislabeled images. A tiered workflow using a probability score of < 0.99 as a cutoff would include 27.6% of the 3004 images for human review and reduce the error rate from 11.7% to 1.5%., Conclusions: The implementation of AI algorithms requires measures in addition to model validation. Tools to flag potential errors in the labels generated by AI models will reduce inaccuracies, increase trust in the system, and provide data for continuous model development., (© 2022 by the American Academy of Ophthalmology.)

Introduction: Explore the impact of the Lung Cancer Screening Trial (NLST-September-2011) and the Medicare approval for CT-screening (CT-LCS-AP-February-2015) on lung cancer incidence rates, mortality, and the percentage of early-stage lung cancer diagnosis (ESLCD-T1-T2N0M0)., Methods: Retrospective interrupted time series analysis using SEER-18 database. All individuals with lung cancer (LC) diagnosis from 2006 to 2016 were included. The effect of NLST and CT-AP-2015 on the monthly percentage of early-stage ESLCD was the primary outcome, additionally LC incidence and mortality rates were calculated. The analysis was performed by age, sex, race, marital status, insurance status, and household income. Bivariate and multivariate models were used to identify predictors of ESLCD., Results: The study cohort was composed by 388,207 individuals, 69 years old in average, 46.6 % female, and 81.1 % white. LC incidence and mortality rates declined from 2006 to 2016 without association with NLST-September-2011 and CT-LCS-AP-February-2015. The percentage of ESLCD increased over time for all groups. Overall rates of ESLCD started at 18 % in January-2006 and increased to 25 % by December-2016. The intervention NLST-2011 did not show an impact in the ESLCD while the CT-AP-2015 showed a significant impact in the ESLCD trend (p < 0.001). ESLCD was associated with female, white, insurance, and household incomes above median. Medicare expansion was a significant factor for insured group, married patients and those from households under the median income level., Conclusion: Medicare approval for CT screening was found to have a statistically significant effect on the diagnosis of early-stage lung cancer and neither NLST-September-2011 nor CT-AP-2015-February-2015 impacted the incidence nor mortality rates., Policy Summary: To improve early-stage lung cancer diagnosis, it is vital to invest in health policies to increase Lung Cancer Screening implementation and to reduce disparities in access to diagnosis. Furthermore, policies that facilitate access to diagnosis and treatment are crucial to reduce lung cancer mortality., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Purpose: To identify the incidence, preoperative risk factors, and prognosis associated with pathologically positive lymph node (pN+) in patients undergoing a sub-lobar resection (SLR). Methods: This is a retrospective study using the National Cancer Database (NCDB) from 2004 to 2014 analyzing SLR excluding those with any preoperative chemotherapy and/or radiation, follow-up <3 months, stage IV disease, or >1 tumor nodule. Multivariable modeling (MVA) was used to determine factors associated with overall survival (OS). Propensity score matching (PSM) was used to determine preoperative risk factors for pN+ in patients having at least one node examined to assess radiation's effect on OS in those patients with pN+ and to determine whether SLR was associated with inferior OS as compared to lobectomy for each nodal stage. Results: A total of 40,202 patients underwent SLR, but only 58.3% had one lymph node examined. Then, 2,615 individuals had pN + which decreased progressively from 15.1% in 2004 to 8.9% in 2014 (N1, from 6.3 to 3.0%, and N2, from 8.4 to 5.9%). A lower risk of pN+ was noted for squamous cell carcinomas, bronchioloalveolar adenocarcinoma (BAC), adenocarcinomas, and right upper lobe locations. In the pN+ group, OS was worse without chemotherapy or radiation. Radiation was associated with a strong trend for OS in the entire pN+ group ( p = 0.0647) which was largely due to the effects on those having N2 disease ( p = 0.009) or R1 resections ( p = 0.03), but not N1 involvement ( p = 0.87). PSM noted that SLR was associated with an inferior OS as compared to lobectomy by nodal stage in the overall patient population and even for those with tumors <2 cm. Conclusion: pN+ incidence in SLRs has decreased over time. SLR was associated with inferior OS as compared to lobectomy by nodal stage. Radiation appears to improve the OS in patients undergoing SLR with pN+, especially in those with N2 nodal involvement and/or positive margins., (Copyright © 2020 Varlotto, Emmerick, Voland, DeCamp, Flickinger, Maddox, Herbert, Griffin, Rava, Fitzgerald, Oliveira, Baima, Sood, Walsh, McIntosh, Lou, Maxfield, Rassaei and Uy.)

Objectives: Programmed death-ligand 1 (PD-L1) expression is a biomarker for cancer immunotherapy. Diabetes mellitus type-2 is a comorbid disease associated with adverse outcomes in Non-Small Cell Lung Cancer (NSCLC). We aimed to investigate the differences in PD-L1 expression in diabetics., Methods: A matched case-control cohort of surgically-resected NSCLC was assembled from an early multicenter study (PMID: 19152440). PD-L1 immunohistochemistry (Clone 22C3) was graded by a tumor positive score (TPS) system (TPS0: no staining; TPS1: <1%; TPS2: 1-49%; TPS3: ≥50%). Variables showing significance at univariate survival analysis were fit in a Cox regression survival model., Results: Diabetics (n=40) and nondiabetics (n=39) showed no differences in age, gender, cancer stage, and follow-up. NSCLCs were more likely PD-L1 positive in diabetics but with tumor positivity <50% (TPS0: 7.5 vs. 20.5%, TPS1: 35 vs. 25.6%, TPS2: 45 vs.23.1%, TPS3: 12.5 vs. 30.8%, respectively; P<0.05). In diabetics, squamous cell carcinomas (SCC) and adenocarcinomas were mainly TPS2 (65% vs. 20%) and TPS1 (50% vs. 26%), respectively. Peritumoral inflammation correlated with TPS (r=0.228), a relationship accentuated in diabetics (r=0.377, P<0.05) but diminished and non-significant in nondiabetics (r=0.136, P≥0.05). This association was stronger in SCC (r=0.424). Diabetes was associated with increased tumor recurrence (HR: 3.08; 95%CI: 1.027-9.23)., Conclusion: Diabetes is associated with an increase in peritumoral inflammation, PD-L1 positivity, and recurrence in NSCLC, more pronounced in SCC, suggesting the possibility of metabolic reprogramming and upregulation of PD-L1 by inducible pathways., (Copyright © 2020 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

To investigate the interrelation between economic, marital, and known histopathologic/therapeutic prognostic factors in presentation and survival of patients with lung cancer in nine different ethnic groups. A retrospective review of the SEER database was conducted through the years 2007-2012. Population differences were assessed via chi-square testing. Multivariable analyses (MVA) were used to detect overall survival (OS) differences in the total population (TP, N = 153,027) and for those patients presenting with Stage IV (N = 70,968). Compared to Whites, Blacks were more likely to present with younger age, male sex, lower income, no insurance, single/widowed partnership, less squamous cell carcinomas, and advanced stage; and experience less definitive surgery, lower OS, and lung cancer-specific (LCSS) survival. White Hispanics presented with younger age, higher income, lower rates of insurance, single/widowed partnership status, advanced stage, more adenocarcinomas, and lower rates of definitive surgery, but no difference in OS and LCSS than Whites. In the TP and Stage IV populations, MVAs revealed that OS was better or equivalent to Whites for all other ethnic groups and was positively associated with insurance, marriage, and higher income. Blacks presented with more advanced disease and were more likely to succumb to lung cancer, but when adjusted for prognostic factors, they had a better OS in the TP compared to Whites. Disparities in income, marital status, and insurance rather than race affect OS of patients with lung cancer. Because of their presentation with advanced disease, Black and Hispanics are likely to have increased benefit from lung cancer screening., (© 2018 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.)

Purpose: To investigate the relationship between serum 25-hydroxyvitamin D (25[OH]D) levels and nuclear cataract among participants of the Carotenoids in Age-Related Eye Disease Study (CAREDS), an ancillary study of the Women's Health Initiative (WHI) Observational Study (OS)., Methods: Nuclear cataract was assessed from slit lamp photographs (2001-2004) taken 6 years after collecting serum analyzed for 25(OH)D levels at WHI baseline (1994-1998) in 1278 CAREDS participants age 50 to 79 years. Multivariate (age, iris color, smoking, pulse pressure) odds ratios (ORs) for nuclear cataract (nuclear opacities > level 4 or cataract extraction) by quintiles of serum 25(OH)D were estimated using logistic regression., Results: No significant association was observed between serum 25(OH)D and nuclear cataract among women of all ages (age-adjusted OR [95% confidence interval (CI)] 0.97 [0.65-1.45]). However, there was a significant age interaction (P for interaction = 0.04). There were no significant associations in the women 70 years or older. In women younger than 70 years, we observed an inverse association between serum 25(OH)D and nuclear cataract (multivariate adjusted ORs [95% CI] 0.54 [0.29-0.99] and 0.66 [0.36-1.20] for quintiles 4 and 5 vs. 1, respectively; P = 0.03). Further adjustment for 25(OH)D determinants (body mass index, vitamin D intake, and UVB exposure) attenuated this association., Conclusions: Serum 25(OH)D levels were unrelated to nuclear opacities in this study sample. However, exploratory analyses suggest a protective association in women younger than 70 years. Further investigations of the relationship between vitamin D and nuclear lens opacities are warranted.

Objective: The relationship between serum 25-hydroxyvitamin D (25[OH]D) concentrations (nmol/L) and the prevalence of early age-related macular degeneration (AMD) was investigated in participants of the Carotenoids in Age-Related Eye Disease Study., Methods: Stereoscopic fundus photographs, taken from 2001 to 2004, assessed AMD status. Baseline (1994-1998) serum samples were available for 25(OH)D assays in 1313 women with complete ocular and risk factor data. Odds ratios (ORs) and 95% confidence intervals (CIs) for early AMD (n = 241) of 1287 without advanced disease were estimated with logistic regression and adjusted for age, smoking, iris pigmentation, family history of AMD, cardiovascular disease, diabetes, and hormone therapy use., Results: In multivariate models, no significant relationship was observed between early AMD and 25(OH)D (OR for quintile 5 vs 1, 0.79; 95% CI, 0.50-1.24; P for trend = .47). A significant age interaction (P = .002) suggested selective mortality bias in women aged 75 years and older: serum 25(OH)D was associated with decreased odds of early AMD in women younger than 75 years (n = 968) and increased odds in women aged 75 years or older (n = 319) (OR for quintile 5 vs 1, 0.52; 95% CI, 0.29-0.91; P for trend = .02 and OR, 1.76; 95% CI, 0.77-4.13; P for trend = .05, respectively). Further adjustment for body mass index and recreational physical activity, predictors of 25(OH)D, attenuated the observed association in women younger than 75 years. Additionally, among women younger than 75 years, intake of vitamin D from foods and supplements was related to decreased odds of early AMD in multivariate models; no relationship was observed with self-reported time spent in direct sunlight., Conclusions: High serum 25(OH)D concentrations may protect against early AMD in women younger than 75 years.

Objective: To assess the association between healthy diet scores and prevalence of nuclear cataract in women., Methods: The association between healthy diet scores, which reflect adherence to the US dietary guidelines, and prevalence of nuclear cataract determined 4 to 7 years later was assessed in a sample of Women's Health Initiative Observational Study participants (aged 50-79 years) residing in Iowa, Wisconsin, and Oregon. Scores on the 1995 Healthy Eating Index, which reflect adherence to 1990 guidelines, were assigned from responses to food frequency questionnaires at the Women's Health Initiative baseline (1994-1998). Presence of nuclear cataract was determined from slitlamp photographs and self-reports of cataract extractions were assessed from May 1, 2001, to January 31, 2004, in 1808 women participating in the Carotenoids in Age-Related Eye Disease Study., Results: Having a high 1995 Healthy Eating Index score was the strongest modifiable predictor of low prevalence of nuclear cataract among numerous risk factors investigated in this sample. The multivariate-adjusted odds ratio for high vs low quintile for diet score was 0.63 (95% confidence interval, 0.43-0.91). Higher prevalence of nuclear cataract was also associated with other modifiable factors (smoking and marked obesity) and nonmodifiable factors (having brown eyes, myopia, and high pulse pressure). Vitamin supplement use was not related to cataract., Conclusion: These data add to the body of evidence suggesting that eating foods rich in a variety of vitamins and minerals may contribute to postponing the occurrence of the most common type of cataract in the United States.

In this study, we examined the impact of long-term (>8 y), low-fat, high-fruit and -vegetable diets on levels of lutein and zeaxanthin in the macula of the retina, as indicated by the OD of macular pigment. Macular pigment OD, measured by heterochromatic flicker photometry, was compared in women aged 60-87 y, who, 7-18 mo earlier (median 12 mo), had been in the dietary modification intervention (n = 158) or comparison (n = 236) groups of the Women's Health Initiative (WHI) at the Madison, WI site for a mean of 8.5 y. Women in the intervention group ate more fruits and vegetables (mean +/- SEM) (6.1 +/- 0.2 vs. 4.6 +/- 0.2 servings/d; P < 0.0001) and had higher intakes of lutein and zeaxanthin from foods and supplements (2.7 +/- 0.2 vs. 2.1 +/- 0.1 mg/d; P = 0.0003) than the comparison group. However, macular pigment density did not differ between the intervention (0.36 +/- 0.02 OD units) and comparison (0.35 +/- 0.01 OD units) groups. It tended to be higher (11%; P = 0.11) in women consuming lutein and zeaxanthin in the highest compared with the lowest quintile (median 6.4 vs. 1.1 mg/d). The increase in fruit and vegetable intake among dietary modification participants of this WHI subsample was not of sufficient magnitude to alter the mean density of retinal carotenoids, given other existing dietary conditions in this sample.

Objective: To evaluate associations between nuclear cataract (determined from slitlamp photographs between May 2001 and January 2004) and lutein and zeaxanthin in the diet and serum in patients between 1994 and 1998 and macula between 2001 and 2004., Design: A total of 1802 women aged 50 to 79 years in Iowa, Wisconsin, and Oregon with intakes of lutein and zeaxanthin above the 78th (high) and below the 28th (low) percentiles in the Women's Health Initiative Observational Study (1994-1998) were recruited 4 to 7 years later (2001-2004) into the Carotenoids in Age-Related Eye Disease Study., Results: Women in the group with high dietary levels of lutein and zeaxanthin had a 23% lower prevalence of nuclear cataract (age-adjusted odds ratio, 0.77; 95% confidence interval, 0.62-0.96) compared with those with low levels. Multivariable adjustment slightly attenuated the association (odds ratio, 0.81; 95% confidence interval, 0.65-1.01). Women in the highest quintile category of diet or serum levels of lutein and zeaxanthin as compared with those in the lowest quintile category were 32% less likely to have nuclear cataract (multivariable-adjusted odds ratio, 0.68; 95% confidence interval, 0.48-0.97; P for trend = .04; and multivariable-adjusted odds ratio, 0.68; 95% confidence interval, 0.47-0.98; P for trend = .01, respectively). Cross-sectional associations with macular pigment density were inverse but not statistically significant., Conclusions: Diets rich in lutein and zeaxanthin are moderately associated with decreased prevalence of nuclear cataract in older women. However, other protective aspects of such diets may in part explain these relationships.

Due to high incidence and quality-of-life impact, upper respiratory infection substantially impacts on population health. To test or compare treatment effectiveness, a well-designed and validated illness-specific quality-of-life instrument is needed. Data reported in the current study were obtained from a trial testing echinacea for induced rhinovirus infection. Laboratory-assessed biomarkers included interleukin (IL)-8, nasal neutrophil count (polymorphonuclear neutrophils (PMN)), mucus weight, viral titre and seroconversion. The questionnaires used included the general health short form (SF)-8 (24-h recall version), the eight-item Jackson cold scale, and the 44-item Wisconsin Upper Respiratory Symptom Survey (WURSS). In total, 399 participants were inoculated with rhinovirus and monitored over 2,088 person-days. Statistically significant associations were found among nearly all variables. Between-questionnaire correlations were: WURSS-Jackson = 0.81; WURSS-SF-8 = 0.62; and Jackson-SF-8 = 0.60. Correlations with laboratory values were as follows: WURSS-mucus weight = 0.53; Jackson-mucus weight = 0.55; WURSS-viral titre = 0.37; Jackson-viral titre = 0.46; WURSS-IL-8 = 0.31; Jackson-IL-8 = 0.36; WURSS-PMN = 0.31; and Jackson-PMN = 0.28. Neither WURSS nor Jackson yielded satisfactory cut-off scores for diagnosis of infection. Symptomatic and biological outcomes of upper respiratory infection are highly variable, with only modest associations. While Wisconsin Upper Respiratory Symptom Survey and Jackson questionnaires both correlate with biomarkers, neither is a good predictor of induced infection. The inclusion of functional and quality-of-life items in the Wisconsin Upper Respiratory Symptom Survey does not significantly decrease the strength of association with laboratory-assessed biomarkers.

The efficacy of fungicides in controlling cottonball disease of cranberry was tested during 1996 to 1998 at three locations in Wisconsin. For some fungicides, the efficacy of four applications, two each during shoot elongation and bloom, was compared with two applications during bloom only. Spraying twice during bloom was as effective in controlling secondary infection as spraying twice during shoot elongation plus twice during bloom. Azoxystrobin, cyprodinil, and propiconazole were equally effective. None of the treatments affected yield, fruit retention, or berry weight compared with the controls. Sensitivity of M. oxycocci, the cottonball pathogen, to fenbuconazole and propiconazole was tested in vitro by comparing the distributions of ED 50 values of populations collected from three sites that differed in previous exposure to fungicides. Median ED 50 values for fenbuconazole were significantly greater at sites where sterol demethylation inhibitor fungicides had been used compared with a site where fungicides had never been used, but median ED 50 values for propiconazole did not differ among sites. There was no correlation between the sensitivities to fenbuconazole and propiconazole. The data will form the basis of recommendations aimed at delaying the onset of fungicide resistance and will provide a baseline for monitoring resistance to fenbuconazole and propiconazole in populations of M. oxycocci in the future.