Generate an explanation for the given claim using the provided supporting material from the paragraph. Please consider the following points while generating an output. 1) The claim will always have supporting proof in the paragraph, and the paragraph will have a clear point of view supporting the claim. 2) There can be instances where direct correlation to the claim is not available. Make use of the sentences in the paragraph to provide a corresponding output supporting the claim. 3) The explanation should be at least one and at most twelve sentences long.

Example Input: Paragraph: The company said the trial will continue unchanged as per the recommendation of a data monitoring committee. The trial was testing Bristol-Myers’ drugs Opdivo and Yervoy, against Opdivo alone, in patients with advanced melanoma. The combination failed to show a statistically significant benefit in patients whose tumors had 1% or lower levels of the PD-L1 protein being targeted, the company said. The American Cancer Society estimates that about 96,480 melanoma cases will be diagnosed in the United States this year. Bristol-Myers shares were trading at $55.99 before the bell. Claim: Bristol-Myers misses main goal of late-stage skin cancer trial.
Example Output: Bristol-Myers Squibb Co said on Wednesday a late-stage trial testing a combination of its cancer drugs missed a main goal of preventing skin cancer from recurring in a certain group of patients, sending its shares down nearly 1%.

Example Input: Paragraph: Costs are mentioned reasonably early in the story, and with specificity. This was good to see. Benefits of these tests are touted, but not quantified. An officer of the National Ovarian Cancer Research Fund Alliance, an advocacy group, testifies that the outcomes of women who have surgery from a gynecologic oncologist “are much better.” But we don’t know what that means. Is it longer survival? Later the story explains that combining the two blood tests with assessment by a clinician “better determined the patients who should be referred to a [gynecological oncologist], identifying well over 90 percent of the women who actually had cancer.”  (Note that this statistic reflects only referral to a gyn-onc, not patient survival.) But how does that compare to the standard assessment tools? A 2016 study described as publication “of the first clinical utility data” demonstrating that use of OVA1 resulted in referral of ovarian patients to gynecologic oncologists offers similar outcomes but is not mentioned in the story. We’re told that experts fear that these tests could lead to unnecessary surgery or delayed diagnosis, and that’s sufficient for a Satisfactory rating. The story could have delved into a bit more of the specifics: What is the evidence for these concerns? What are the false positive and false negative rates? These details are useful because the point of the story is that clinicians are not using these tests to try to improve outcomes of ovarian cancer patients. Are the possible debits–or uncertainties driven by lack of clinical data–contributing to these decisions? There isn’t sufficient information on the evidence behind these tests. The FDA has approved ROMA and OVA1 for use, but the studies that led to that decision are not discussed. Nor is there sufficient discussion of why the physician groups that write guidelines haven’t endorsed the tests. Their concerns are raised, but the evidence is not presented or analyzed. A late diagnosis of ovarian cancer is way too common, and the outcome is grim. At the same time, the anecdotes seem to highlight the sad aspect of the disease without necessarily providing a relevant case in which the tests described would have helped (any more than a basic blood test would have). The companies responsible for developing and marketing these two tests are front and center in this story, with scientists affiliated with the companies clearly identified. At least two sources in the story—one of them a scientist affiliated with the National Comprehensive Cancer Network—appear to be independent of the companies. The story makes it clear that no effective early detection screening test exists. Existing strategies—the CA125 blood test and vaginal ultrasound—are mentioned and then discounted, in part via a personal narrative of a young woman who received a late diagnosis of cancer. While data-driven specifics aren’t included on why standard methods aren’t sufficient, this is enough to rate Satisfactory. A direct comparison of survival stemming from existing diagnostic tests relative to survival stemming from ROMA and OVA1 would have strengthened the story. If those numbers aren’t available, that should have been pointed out. The story makes it clear that the two blood tests have been available since 2009. The story mentions that the tests are combinations of existing tests with a “proprietary” formula (essentially a risk prediction tool) to translate the results to likelihood of cancer. But, the article should have talked about whether the tests, other than CA-125, have been used before. This appears to be an enterprise story, and does not rely on a news release. Claim: Ovarian cancer blood tests: Available, not widely used
Example Output: This is a story about the apparent underuse of two blood tests—ROMA and OVA1—that are FDA approved to help clinicians decide whether surgery to investigate abnormal growths should be performed by a gynecologic oncologist (“gyn-onc”) trained to remove malignant ovarian cancer, rather than an obstetrician-gynecologist or a general surgeon. The gist of the story is that the tests have not been widely adopted in the ensuing years, “largely because they haven’t been recommended by the physician groups that write the care guidelines.” The story hit on a lot of important notes–it told readers the cost of these tests, and it included comments from independent sources. What is not clear is the extent to which clinical evidence supports the increased use of the two tests. We’re told they accurately picked up about 90 percent of cancer cases. But we’re not told how that compares to standard methods of detection. As the story notes, surviving ovarian cancer is an uphill battle–it is often a deadly disease caught too late. Any procedure that increases the probability of survival is worth careful consideration.

Example Input: Paragraph: "In the Sunday, Feb. 13, 2011, installment of the comic strip Doonesbury, Mark Slackmeyer -- a longtime character in the strip who is a liberal radio host -- makes a point about gun violence. ""What are we like as a people?"" Slackmeyer muses to himself in his studio. ""Nine years, ago we were attacked -- 3,000 people died. In response, we started two long, bloody wars and built a vast homeland-security apparatus -- all at a cost of trillions! Now consider this. During those same nine years, 270,000 Americans were killed by gunfire at home. Our response? We weakened our gun laws."" At that point, a whirring sound comes from off-panel. In the final panel, we see that his guest is a space alien, who says, ""Fail. Cannot Comprehend."" To which Slackmeyer cracks, ""Well, you may be a little jet-lagged."" A reader asked us to fact-check it. So we’ll look at whether since Sept. 11, 2001, ""270,000 Americans were killed by gunfire at home."" We began by contacting Garry Trudeau, the cartoonist who has drawn Doonesbury for more than four decades. He got back immediately with a summary of his methodology. ""The final figure lacks precision, because it's extrapolated,"" Trudeau wrote us, noting, correctly, that the most recent data for gun deaths from the Centers for Disease Control and Prevention is from 2007. ""What I had were six years -- 2002-2007 -- of a remarkably stable number, around 30,000"" gun deaths per year, Trudeau wrote. ""So in my judgment, multiplying 30,000 times nine yielded a figure reasonable and accurate enough for rhetorical purposes without using hyperbole. If anything, it may be slightly on the low side."" We found that Trudeau was basically right. We went to the same CDC database he used -- the Web-based Injury Statistics Query and Reporting System (or WISQARS for short) -- and got virtually identical numbers. Our number came out slightly higher -- 281,757 -- because we not only extrapolated out through the end of 2010 in our calculations but also included the final three months of 2001. We should note the details of Trudeau’s definition of gun deaths, which is also the definition we would have used if we’d been starting from scratch. It includes the following categories:  • Suicides: 102,002 between 2002 and 2007 • Homicides: 73,148 between 2002 and 2007 • Accidental: 4,185 between 2002 and 2007 • Legal shootings: 1,999 between 2002 and 2007 • Undetermined: 1,427 between 2002 and 2007  -- Total: 182,761 between 2002 and 2007  So on the numbers, Trudeau’s methodology was accurate. The only thing that threw us was how the strip had described where the deaths occurred -- ""270,000 Americans were killed by gunfire at home"" (our emphasis). Initially, we took that to mean that 270,000 Americans were literally killed in or near their homes. And we knew that couldn’t be right, because the number both we and Trudeau calculated included all gunfire deaths, wherever they had occurred. When we asked criminologists for guidance on what percentage of gun deaths occur at home, they said the statistics on that question are scattershot. James Alan Fox, a criminologist at Northeastern University, provided data on Chicago homicides from an amicus brief he wrote for a Supreme Court case. Since 1965, the ratio of outside-the-home handgun homicides in Chicago to those occurring at home has tended to bounce around from about two-to-one in the 1970s to about five-to-one in the 1990s. So if one interprets ""at home"" to mean in or near someone’s home, the numbers Trudeau calculated wouldn’t be correct. When we raised this point with Trudeau, he said that wasn’t what he meant: ""I didn't say ‘in the home,’ I said ‘at home’ as opposed to abroad, where the wars are. Failure to communicate clearly, I guess. Rats."" Reading through it again, we think Trudeau’s explanation sounds reasonable. But we decided to mark Trudeau down slightly because we think it’s also reasonable for people to make the same initial assumption we did, that ""at home"" means in or near one’s home. So we’ll rate the comment ." Claim: "Since Sept. 11, 2001, ""270,000 Americans were killed by gunfire at home."
Example Output:
Doonesbury strip says 270,000 Americans have been killed by guns since 9/11